Online Course in Business Information Technology

Best Online Courses in Business Information Technology 2017

Business Information Technology

Student who would prefer to learn online may do so by enrolling in an online course. This particular course is much like its on-campus counterpart, but all course materials, lessons and tests are typically offered through a web-based platform.

What is an online course in business information technology? This class is an interdisciplinary exploration of the technologies and practices commonly used by businesses to handle information, communicate and process data. As such, many topics will likely be covered, with the curriculum focusing primarily on the web, hardware and software applications that are most vital to businesses’ functions. After exploring these basic principles, the class may delve into the problems and potential solutions commonly encountered when working with such technologies.

Any student who has an interest in business, technology or computing can benefit from this online course’s exploration of the topics in an intersecting context. The unique approach may develop students’ specialized knowledge and equip them for entry into promising careers.

The cost of enrollment for this online course is dependent upon many different factors. If you are in need of an estimate, the admissions office is the best source for one. You can also inquire about scholarships and financial aid.

Some of the careers that may be relevant to a course in business information technology include IT specialist, computer support specialist, programmer and business application developer. All these apply the intersectional knowledge developed in the course and provide students with the opportunity to exercise multiple skill sets. Because technology is rapidly evolving, there are sure to be many more positions that develop and become available for qualified students.

If you are interested in enrolling in a business information technology course, you school may offer one through online study. Search for your program below and contact directly the admission office of the school of your choice by filling in the lead form.

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Data Analytics with R Certification Training

Edureka
Online Full time Part time 12 days Open Enrollment India India Online + 1 more

The Edureka Mastering Data Analytics with R training course is specially designed to provide the requisite knowledge and skills to become a successful analytics professional. It starts with the fundamental concepts of Data Manipulation, Exploratory Data Analysis etc before moving over to advance topics like [+]

Top Online Courses in Business Information Technology. About the Course The Edureka Mastering Data Analytics with R training course is specially designed to provide the requisite knowledge and skills to become a successful analytics professional. It starts with the fundamental concepts of Data Manipulation, Exploratory Data Analysis etc before moving over to advance topics like the Ensemble of Decision trees, Collaborative filtering, etc. Course Objectives After the completion of the Edureka Mastering Data Analytics with R course, you should be able to: Understand concepts around Business Intelligence and Business Analytics Explore Recommendation Systems with functions like Association Rule Mining , user-based collaborative filtering and Item-based collaborative filtering among others Apply various supervised machine learning techniques Perform Analysis of Variance (ANOVA) Learn where to use algorithms - Decision Trees, Logistic Regression, Support Vector Machines, Ensemble Techniques etc Use various packages in R to create fancy plots Work on a real-life project, implementing supervised and unsupervised machine learning techniques to derive business insights Who should go for this Course? This course is meant for all those students and professionals who are interested in working in analytics industry and are keen to enhance their technical skills with exposure to cutting-edge practices. This is a great course for all those who are ambitious to become 'Data Analysts' in near future. This is a must learn course for professionals from Mathematics, Statistics or Economics background and interested in learning Business Analytics. What are the pre-requisites for this Course? The pre-requisites for learning 'Mastering Data Analytics with R' include basic statistics knowledge. We provide a complimentary course "Statistics Essentials for R" to all the participants who enroll for the Data Analytics with R Training. This course helps you brush up your statistics skills. Project Work Towards the end of the Course, you will be working on a live project. You can choose any of the following as your Project work: Project #1: Sentiment Analysis of Twitter Data Industry : Social Media Description : A sports gear company is planning to brand themselves by putting their company logo on the jersey of an IPL team. We assume that any team which is more popular on twitter will give a good ROI. So, we evaluate two different teams of IPL based on their social media popularity and the team which is more popular on twitter will be chosen for brand endorsement. The data to be analyzed is streamed live from twitter and sentiment analysis is performed on the same. The final output involves a comparable visualization plot of both the teams, so that the clear winner can be seen. The following insights need to be calculated : Setup connection with twitter using twitter package. And perform authentication using handshake function. Import tweets from the official twitter handle of the two teams using SearchTwitter function. Prepare a sentiment function in R, which will take the arguments and find its negative or positive score. Score against each tweet should be calculated. Compare the scores of both the teams and visualize it. Project #2: Census Data Analysis Industry : Government Dataset Description : Analyze the census data and predict whether the income exceeds $50K per year. Follow end to end modelling process involving: Perform Exploratory Data Analysis and establish hypothesis of the data. Test for Multi col-linearity, handle outliers and treat missing data. Create training and validation data sets using Stratified Random Sampling (SRS) of data. Fit Classification model on training set (Logistic Regression/Decision Tree) Perform validation of the models (ROC curve, Confusion Matrix) Evaluate and freeze the final model. Additional Resources: Here is the list of few additional case studies that you will get at edureka for deeper understanding of R applications. Study#1: Market Basket Analysis Industry: Retail - CPG Description: Market Basket Analysis is done to see if there are combinations of products that frequently co-occur in transactions. The analysis gives clues as to what a customer might have bought if the idea had occurred to them. This is done using the “Association Rules” on real-time data. In this case study, you shall understand various methods for finding useful associations in large data sets using statistical performance measures. You will also learn how to manage the peculiarities of working with transaction data. Data-set: The data set used here is from a grocery super store with 9835 rows of free flowing data without any labels. Study#2: Strategic Customer Segmentation for Retail Business Industry: E-Commerce, Retail Description: In this case study, we will consider the dataset from a UK-based online retail business for the last two years. The objective of this case study is to do customer segmentation in this data set. For this exercise, we are going to use customer’s recency, frequency and monetary (RFM) values. From these three derived values, we will segment entire customer base and will generate insights on the data set provided to do customer segmentation using RFM Model based Clustering Analysis. Data-set: comprises 0.5 million records and 8 variables. Each record is for one online order placed by the customer. Study#3: Pricing Analytics and Price Elasticity Industry: Retail Description: A retailer is planning to sell a new type of cheese in some of its stores. This is a pilot project for the retailer & based on the data collected during this pilot phase, retailer wants to understand a few things. To promote sales of cheese, the retailer is planning for two different types of in-store advertisement: Cheese as a natural product Cheese as a family caring product Now the retailer wants to know: Which in-store advertisement theme is better and giving better sales of cheese in the store? How the sales of cheese is reacting to its price change i.e. price elasticity? What is the impact of the price changes of other products in the same store (e.g. Ice-cream & Milk) on the sales of cheese i.e. cross-price elasticity. What should be the best price of cheese to maximize the sales and then do sales forecast. Data-set: The data set used in this case study will have the following columns - Price of Cheese Sales of Cheese Advertising method for cheese (either as a natural product or as a family product) Price of Ice cream Price of Milk Study#4: Clustering Application using Shiny Industry: Consumer Packaged Goods Description: Shiny turn your analyses into interactive web applications, it is a web application framework for R. The data set that we are using in this case study relates to the clients of a wholesale distributor. It comprises, the annual spending in monetary units (m.u.) on diverse product categories. With this data we want to create a web based shiny application which can segment customers of wholesale distributor based upon the parameter passed thru ui.r Data-set: The data set used in this case study has 440 rows of data and has the following attributes in columns - Channel Region Fresh Milk Grocery Frozen Detergents_Paper Delicatessen Why learn Data Analytics with R? The Data Analytics with R training certifies you in mastering the most popular Analytics tool. "R" wins on Statistical Capability, Graphical capability, Cost, rich set of packages and is the most preferred tool for Data Scientists. Below is a blog that will help you understand the significance of R and Data Science: www.edureka.co/blog/r-programming-for-data-science Course Features Online Classes: 24 Hrs 12 live classes of 2 hrs each by Industry practitioners Assignments: 30 Hrs Personal assistance/installation guides for setting up the required environment for Assignments / Projects Project: 25 Hrs Live project in Data Analytics using techniques of Regression, Predictive Analytics, Data Mining, etc. Lifetime Access Lifetime access to the learning management system including Class recordings, presentations, sample code and projects 24 x 7 Support Lifetime access to the support team (available 24/7) in resolving queries during and after the course completion Get Certified Edureka certified 'Data Analyst' based on your project performance, reviewed by our expert panel [-]

Informatica PowerCenter 9.x Certification Training

Edureka
Online Full time Part time 21 days Open Enrollment India India Online + 1 more

Edureka's Informatica PowerCenter 9.X Developer & Admin Course, will introduce the participants to work with the PowerCenter. Developers can use Informatica to create, execute, as well as administer, monitor and schedule ETL processes and understand how these are used in data mining operations. [+]

About The Course Edureka's Informatica PowerCenter 9.X Developer & Admin Course, will introduce the participants to work with the PowerCenter. Developers can use Informatica to create, execute, as well as administer, monitor and schedule ETL processes and understand how these are used in data mining operations. The course will also cover Installation & Configuration of Informatica PowerCenter 9.X and basic Administration Activities. Participants will also get to implement one project towards the end of the course. Course Objectives After the completion of the Informatica course at Edureka, you will be able to : Understand and identify different Informatica Products Describe Informatica PowerCenter architecture & its different components Use PowerCenter 9.x components to build Mappings, Tasks, Workflows Describe the basic and advanced features functionalities of PowerCenter 9.X transformations Understand Workflow Task and job handling Describe Mapping Parameter and Variables Perform debugging, troubleshooting, error handling and recovery Learn to calculate cache requirement and implement session cache Execute performance tuning and Optimization Recognize and explain the functionalities of the Repository Manager tool. Identify how to handle services in the Administration Console Understand techniques of SCD, XML Processing, Partitioning, Constraint based loading and Incremental Aggregation Gain insight on ETL best practices using Informatica Who should go for this course? The following professionals can go for this course : Software Developers Analytics Professionals BI/ETL/DW Professionals Mainframe developers and Architects Individual Contributors in the field of Enterprise Business Intelligence Pre-requisites The pre-requisites for this course include knowledge of SQL and basic Unix. Project Work Towards the end of the Course, you will be working on a live project to perform data analytics. Project #1 : Creation of Sales Data Warehouse Industry : Retail Data : NorthWind/AdventureWorks dataset. Problem Statement : Creation of ETL jobs to build Sales Data Mart using Informatica. Project #2 : Transaction Analysis for Retail Industry : Retail Data : Sales data from Real time retail project. ( Data will be masked) Problem Statement : Analyzing Retail Transaction Information using Informatica. Why learn Informatica? Informatica provides the market's leading data integration platform. Tested on nearly 500,000 combinations of platforms and applications, the data integration platform inter operates with the broadest possible range of disparate standards, systems, and applications. This unbiased and universal view makes Informatica unique in today's market as a leader in the data integration platform. It also makes Informatica the ideal strategic platform for companies looking to solve data integration issues of any size. Course Features Online Classes: 42 Hrs There will be 12 instructor-led interactive online classes during the course. Each class will be of approximately 3.5 hours and will happen at the scheduled time of the batch you choose. You have the flexibility to reschedule your class in a different batch if you miss any class. Class recordings will be uploaded in the LMS after the class. The access to class recordings is lifetime. Assignments: 25 Hrs Each class will be followed by practical assignments which can be completed before the next class. These assignments will help in applying the concepts taught in the Live classes. Our 24x7 expert support team is available to help you through Email, phone or Live support for any issues you may face during the Lab Hours. Project: 20 Hrs Towards the end of the course, you will be working on a project where you are expected to implement the techniques learnt during the course to visualize and analyze data. Lifetime Access You get lifetime access to the Learning Management System (LMS). All the class recordings, installation guides, class presentations, sample codes, project documents are available in downloadable format in the LMS. Also, your login will never get expired. 24 x 7 Support We have 24x7 online support team available to help you with any technical queries you may have during the course. All the queries are tracked as tickets and you get a guaranteed response from a support engineer. If required, the support team can also provide you Live support by accessing your machine remotely. This ensures that all your doubts and problems faced during labs and project work are clarified round the clock. Get Certified Towards the end of the course, you will be working on a project. Edureka certifies you as a Certified Informatica Expert based on the project reviewed by our expert panel. Anyone certified by Edureka will need to demonstrate practical expertise in Informatica. [-]

Microsoft BI Certification Training

Edureka
Online Full time Part time 15 days Open Enrollment India India Online + 1 more

Microsoft BI course is designed to provide insights on different tools in Microsoft Suite (SQL Server Integration Services, SQL Server Analysis Services, SQL Server Reporting Services). It also gives the practical knowledge on DW concepts and how these tools help in developing a robust end-to-end BI solution. [+]

Top Online Courses in Business Information Technology. About The Course Microsoft BI course is designed to provide insights on different tools in Microsoft Suite (SQL Server Integration Services, SQL Server Analysis Services, SQL Server Reporting Services). It also gives the practical knowledge on DW concepts and how these tools help in developing a robust end-to-end BI solution. Course Objectives After the completion of Microsoft BI course at Edureka, you will be able to: Understand DW concepts including ETL and Multidimensional modelling Install and configure end-end MSBI system Implement end-to-end ETL system using SQL Server Integration Services Gain insight on Multidimensional model and its importance Create Cubes and administer them in SSAS Create multiple types of reports and visualizations using SSRS/PowerView etc. Understand the concept and need for ad-hoc reports Apply Microsoft tools like Report Builder, Power View Give an end-to-end picture how Microsoft BI suites various tools work Integrate various BI tools to build a complete BI solution Who should go for this course? This course is designed for professionals aspiring to make a career in Business Intelligence. Software or Analytics professionals having background/experience of any RDBMS, ETL, OLAP or reporting tools are the key beneficiaries of this course. Pre-requisites The pre-requisite for this course is basic understanding of RDBMS. Why learn MSBI? As we move from experience and intuition based decision making to factual decision making, it is increasingly important to capture data and store it in a way that allows us to make smarter decisions. This is where Data warehouse/Business Intelligence comes into picture. There is a huge demand for Business Intelligence professionals and this course acts as a foundation which opens the door to a variety of opportunities in Business Intelligence space. Though there are many vendors providing BI tools, very few of them provide end-end BI suite and huge customer base. Microsoft stands as leader with its user-friendly and cost effective Business Intelligence suite helping customers to get a 360 degree view of their businesses. Course Features Online Classes: 30 Hrs 10 live classes of 3 hrs each by Industry practitioners Assignments: 40 Hrs Personal assistance/installation guides for setting up the required environment for Assignments / Projects Project: 20 Hrs Live project based on designing and developing an end-to-end BI solution using MSBI Suites (SSIS,SSAS,SSRS) Lifetime Access Lifetime access to the learning management system including Class recordings, presentations, sample code and projects 24 x 7 Support Lifetime access to the support team (available 24/7) in resolving queries during and after the course completion Get Certified Edureka certified 'MSBI Expert' based on your project performance, reviewed by our expert panel [-]

Big Data Hadoop Certification Training

Edureka
Online Full time Part time 15 days Open Enrollment India India Online + 1 more

Edureka’s Big Data Hadoop online training is designed to help you become a top Hadoop developer. [+]

Course Details Edureka’s Big Data Hadoop online training is designed to help you become a top Hadoop developer. During this course, our expert instructors will help you: Master the concepts of HDFS and MapReduce framework Understand Hadoop 2.x Architecture Setup Hadoop Cluster and write Complex MapReduce programs Learn data loading techniques using Sqoop and Flume Perform data analytics using Pig, Hive and YARN Implement HBase and MapReduce integration Implement Advanced Usage and Indexing Schedule jobs using Oozie Implement best practices for Hadoop development Work on a real life Project on Big Data Analytics Understand Spark and its Ecosystem Learn how to work in RDD in Spark Who should go for this Hadoop Course? Market for Big Data analytics is growing across the world and this strong growth pattern translates into a great opportunity for all the IT Professionals. Here are the few Professional IT groups, who are continuously enjoying the benefits moving into Big data domain: Developers and Architects BI /ETL/DW professionals Senior IT Professionals Testing professionals Mainframe professionals Freshers Why learn Big Data and Hadoop? Big Data & Hadoop Market is expected to reach $99.31B by 2022 growing at a CAGR of 42.1% from 2015 Forbes McKinsey predicts that by 2018 there will be a shortage of 1.5M data experts Mckinsey Report Avg salary of Big Data Hadoop Developers is $135k Indeed.com Salary Data What are the pre-requisites for the Hadoop Course? As such, there are no pre-requisites for learning Hadoop. Knowledge of Core Java and SQL will be beneficial, but certainly not a mandate. If you wish to brush-up Core-Java skills, Edureka offer you a complimentary self-paced course, i.e. "Java essentials for Hadoop" when you enroll in Big Data Hadoop Certification course. How will I do practicals in Online Training? For practicals, we will help you to setup Edureka's Virtual Machine in your System with local access. The detailed installation guide will be present in LMS for setting up the environment. In case, your system doesn't meet the pre-requisites e.g. 4GB RAM, you will be provided remote access to the Edureka cluster for doing practical. For any doubt, the 24*7 support team will promptly assist you. Edureka Virtual Machine can be installed on Mac or Windows machine and the VM access will continue even after the course is over, so that you can practice. Case-Studies Towards the end of the course, you will work on a live project where you will be using PIG, HIVE, HBase and MapReduce to perform Big Data analytics. Following are a few industry-specific Big Data case studies that are included in our Big Data and Hadoop Certification e.g. Finance, Retail, Media, Aviation etc. which you can consider foryour project work: Project #1: Analyze social bookmarking sites to find insights Industry: Social Media Data: It comprises of the information gathered from sites like reddit.com, stumbleupon.com which are bookmarking sites and allow you to bookmark, review, rate, search various links on any topic.reddit.com, stumbleupon.com, etc. A bookmarking site allows you to bookmark, review, rate, search various links on any topic. The data is in XML format and contains various links/posts URL, categories defining it and the ratings linked with it. Problem Statement: Analyze the data in the Hadoop ecosystem to: Fetch the data into a Hadoop Distributed File System and analyze it with the help of MapReduce, Pig and Hive to find the top rated links based on the user comments, likes etc. Using MapReduce, convert the semi-structured format (XML data) into a structured format and categorize the user rating as positive and negative for each of the thousand links. Push the output HDFS and then feed it into PIG, which splits the data into two parts: Category data and Ratings data. Write a fancy Hive Query to analyze the data further and push the output is into relational database (RDBMS) using Sqoop. Use a web server running on grails/java/ruby/python that renders the result in real time processing on a website. Project #2: Customer Complaints Analysis Industry: Retail Data: Publicly available dataset, containing a few lakh observations with attributes like; CustomerId, Payment Mode, Product Details, Complaint, Location, Status of the complaint, etc. Problem Statement: Analyze the data in the Hadoop ecosystem to: Get the number of complaints filed under each product Get the total number of complaints filed from a particular location Get the list of complaints grouped by location which has no timely response Project #3: Tourism Data Analysis Industry: Tourism Data: The dataset comprises attributes like: City pair (combination of from and to), adults traveling, seniors traveling, children traveling, air booking price, car booking price, etc. Problem Statement: Find the following insights from the data: Top 20 destinations people frequently travel to: Based on given data we can find the most popular destinations where people travel frequently, based on the specific initial number of trips booked for a particular destination Top 20 locations from where most of the trips start based on booked trip count Top 20 high air-revenue destinations, i.e the 20 cities that generate high airline revenues for travel, so that the discount offers can be given to attract more bookings for these destinations. Project #4: Airline Data Analysis Industry: Aviation Data: Publicly available dataset which contains the flight details of various airlines such as: Airport id, Name of the airport, Main city served by airport, Country or territory where airport is located, Code of Airport, Decimal degrees, Hours offset from UTC, Timezone, etc. Problem Statement: Analyze the airlines’ data to: Find list of airports operating in the country Find the list of airlines having zero stops List of airlines operating with code share Which country (or) territory has the highest number of airports Find the list of active airlines in the United States Project #5: Analyze Loan Dataset Industry: Banking and Finance Data: Publicly available dataset which contains complete details of all the loans issued, including the current loan status (Current, Late, Fully Paid, etc.) and latest payment information. Problem Statement: Find the number of cases per location and categorize the count with respect to reason for taking loan and display the average risk score. Project #6: Analyze Movie Ratings Industry: Media Data: Publicly available data from sites like rotten tomatoes, IMDB, etc. Problem Statement: Analyze the movie ratings by different users to: Get the user who has rated the most number of movies Get the user who has rated the least number of movies Get the count of total number of movies rated by user belonging to a specific occupation Get the number of underage users Project #7: Analyze YouTube data Industry: Social Media Data: It is about the YouTube videos and contains attributes such as: VideoID, Uploader, Age, Category, Length, views, ratings, comments, etc. Problem Statement: Identify the top 5 categories in which the most number of videos are uploaded, the top 10 rated videos, and the top 10 most viewed videos. Apart from these there are some twenty more use-cases to choose: Market data Analysis Twitter Data Analysis Where do our learners come from? Professionals from around the globe have benefited from Edureka's Big Data Hadoop Certification course. Some of the top places that our learners come from include San Francisco, Bay Area, New York, New Jersey, Houston, Seattle, Toronto, London, Berlin, UAE, Singapore, Australia, New Zealand, Bangalore, New Delhi, Mumbai, Pune, Kolkata, Hyderabad and Gurgaon among many. Edureka’s Big Data Hadoop online training is one of the most sought after in the industry and has helped thousands of Big Data professionals around the globe bag top jobs in the industry. This online training includes lifetime access, 24X7 support for your questions, class recordings and mobile access. Our Big Data Hadoop certification also include an overview of Apache Spark for distributed data processing. Course Features Online Classes: 30 Hrs There will be 30hrs of Online Live Instructor-led Classes. Depending on the batch you select, it can be: 10 live classes of 3 hrs each over Weekend or, 15 live classes of 2 hrs each on Weekdays. Assignments: 40 Hrs There are hands-on exercises associated with every module in the course. We anticipate that you will spend minimum 40 hours working on assignments to ensure better assimilation of concepts. Edureka will provide the required setup for doing practicals. Project: 20 Hrs At the end, you'll work on a Real-life Project on any of the selected use cases, involving Big Data Analytics using MapReduce, Pig, Hive, Flume and Sqoop Lifetime Access You get lifetime access to the Learning Management System (LMS). You will be able to access class recordings on LMS and lifetime feature shall also benefit you to get the future upgraded versions without paying any extra fee. 24 x 7 Support We have round the clock support available to help you with any technical queries. All the queries are tracked as tickets and you get a guaranteed response from a support engineer. If required, the support team can also provide you Live support by accessing your machine remotely. Please be assured! Get Certified Towards the end of the course, you will work on a project. Edureka certifies you in Big Data and Hadoop course based on the project reviewed by our expert panel. Anyone certified by edureka will be able to demonstrate practical expertise in Big Data and Hadoop. [-]

Course in Excel to MySQL: Analytic Techniques for Business (Beginner)

Coursera
Online Part time 6 - 7 months Open Enrollment USA USA Online

In this Specialization, you’ll learn to frame business challenges as data questions. You’ll use powerful tools and methods such as Excel, Tableau, and MySQL to analyze data, create forecasts and models, design visualizations, and communicate your insights. In the final Capstone Project, you’ll apply your skills to explore and justify improvements to a real-world business process. [+]

Top Online Courses in Business Information Technology. Formulate data questions, explore and visualize large datasets, and inform strategic decisions. In this Specialization, you’ll learn to frame business challenges as data questions. You’ll use powerful tools and methods such as Excel, Tableau, and MySQL to analyze data, create forecasts and models, design visualizations, and communicate your insights. In the final Capstone Project, you’ll apply your skills to explore and justify improvements to a real-world business process. The Capstone Project focuses on optimizing revenues from residential property, and Airbnb, our Capstone’s official Sponsor, provided input on the project design. Airbnb is the world’s largest marketplace connecting property-owner hosts with travelers to facilitate short-term rental transactions. The top 10 Capstone completers each year will have the opportunity to present their work directly to senior data scientists at Airbnb live for feedback and discussion. Courses Business Metrics for Data-Driven Companies In this course, you will learn best practices for how to use data analytics to make any company more competitive and more profitable. You will be able to recognize the most critical business metrics and distinguish them from mere data. You’ll get a clear picture of the vital but different roles business analysts, business data analysts, and data scientists each play in various types of companies. And you’ll know exactly what skills are required to be hired for, and succeed at, these high-demand jobs. Finally, you will be able to use a checklist provided in the course to score any company on how effectively it is embracing big data culture. Digital companies like Amazon, Uber and Airbnb are transforming entire industries through their creative use of big data. You’ll understand why these companies are so disruptive and how they use data-analytics techniques to out-compete traditional companies. Mastering Data Analysis in Excel Important: The focus of this course is on math - specifically, data-analysis concepts and methods - not on Excel for its own sake. We use Excel to do our calculations, and all math formulas are given as Excel Spreadsheets, but we do not attempt to cover Excel Macros, Visual Basic, Pivot Tables, or other intermediate-to-advanced Excel functionality. This course will prepare you to design and implement realistic predictive models based on data. In the Final Project (module 6) you will assume the role of a business data analyst for a bank, and develop two different predictive models to determine which applicants for credit cards should be accepted and which rejected. Your first model will focus on minimizing default risk, and your second on maximizing bank profits. The two models should demonstrate to you in a practical, hands-on way the idea that your choice of business metric drives your choice of an optimal model. The second big idea this course seeks to demonstrate is that your data-analysis results cannot and should not aim to eliminate all uncertainty. Your role as a data-analyst is to reduce uncertainty for decision-makers by a financially valuable increment, while quantifying how much uncertainty remains. You will learn to calculate and apply to real-world examples the most important uncertainty measures used in business, including classification error rates, entropy of information, and confidence intervals for linear regression. All the data you need is provided within the course, all assignments are designed to be done in MS Excel, and you will learn enough Excel to complete all assignments. The course will give you enough practice with Excel to become fluent in its most commonly used business functions, and you’ll be ready to learn any other Excel functionality you might need in the future (module 1). The course does not cover Visual Basic or Pivot Tables and you will not need them to complete the assignments. All advanced concepts are demonstrated in individual Excel spreadsheet templates that you can use to answer relevant questions. You will emerge with substantial vocabulary and practical knowledge of how to apply business data analysis methods based on binary classification (module 2), information theory and entropy measures (module 3), and linear regression (module 4 and 5), all using no software tools more complex than Excel. Data Visualization and Communication with Tableau One of the skills that characterizes great business data analysts is the ability to communicate practical implications of quantitative analyses to any kind of audience member. Even the most sophisticated statistical analyses are not useful to a business if they do not lead to actionable advice, or if the answers to those business questions are not conveyed in a way that non-technical people can understand. In this course you will learn how to become a master at communicating business-relevant implications of data analyses. By the end, you will know how to structure your data analysis projects to ensure the fruits of your hard labor yield results for your stakeholders. You will also know how to streamline your analyses and highlight their implications efficiently using visualizations in Tableau, the most popular visualization program in the business world. Using other Tableau features, you will be able to make effective visualizations that harness the human brain’s innate perceptual and cognitive tendencies to convey conclusions directly and clearly. Finally, you will be practiced in designing and persuasively presenting business “data stories” that use these visualizations, capitalizing on business-tested methods and design principles. Managing Big Data with MySQL This course is an introduction to how to use relational databases in business analysis. You will learn how relational databases work, and how to use entity-relationship diagrams to display the structure of the data held within them. This knowledge will help you understand how data needs to be collected in business contexts, and help you identify features you want to consider if you are involved in implementing new data collection efforts. You will also learn how to execute the most useful query and table aggregation statements for business analysts, and practice using them with real databases. No more waiting 48 hours for someone else in the company to provide data to you – you will be able to get the data by yourself! By the end of this course, you will have a clear understanding of how relational databases work, and have a portfolio of queries you can show potential employers. Businesses are collecting increasing amounts of information with the hope that data will yield novel insights into how to improve businesses. Analysts that understand how to access this data – this means you! – will have a strong competitive advantage in this data-smitten business world. Increasing Real Estate Management Profits: Harnessing Data Analytics In this final course you will complete a Capstone Project using data analysis to recommend a method for improving profits for your company, Watershed Property Management, Inc. Watershed is responsible for managing thousands of residential rental properties throughout the United States. Your job is to persuade Watershed’s management team to pursue a new strategy for managing its properties that will increase their profits. To do this, you will: (1) Elicit information about important variables relevant to your analysis; (2) Draw upon your new MySQL database skills to extract relevant data from a real estate database; (3) Implement data analysis in Excel to identify the best opportunities for Watershed to increase revenue and maximize profits, while managing any new risks; (4) Create a Tableau dashboard to show Watershed executives the results of a sensitivity analysis; and (5) Articulate a significant and innovative business process change for Watershed based on your data analysis, that you will recommend to company executives. Airbnb, our Capstone’s official Sponsor, provided input on the project design. The top 10 Capstone completers each year will have the opportunity to present their work directly to senior data scientists at Airbnb live for feedback and discussion. "Note: Only learners who have passed the four previous courses in the specialization are eligible to take the Capstone." [-]

SEO for Business - Certified

New Skills Academy
Online Part time 2 hours Open Enrollment United Kingdom UK Online

Right now, potential customers will be searching for your products and services ‐ and if they don’t find their way to your site, you could be deferring them to a competitor. Imagine if your website could rank above your competitors’, using the kind of search terms that turn your visitor traffic into revenue. [+]

Apply Now - Special Offer

Right now, potential customers will be searching for your products and services ‐ and if they don’t find their way to your site, you could be deferring them to a competitor. Imagine if your website could rank above your competitors’, using the kind of search terms that turn your visitor traffic into revenue. When it’s done well, search engine marketing can give search engines exactly what they need to put your website in a prime position on Search Engine Results Pages. The key is understanding what search engines need ‐ and since 90% of all searches in the UK are via Google, this pretty much means understanding Google. This course will explain the proven techniques that will help you reach and maintain the number one results spot. What you will Learn / Course Modules Introduction to SEO Link Building On-Site SEO Social Media as part of SEO Local Search Pay Per Click (PPC) [-]

ITIL® Expert Level - Managing across the Lifecycle (MALC) Training

E-Careers
Online Part time 12 months Open Enrollment United Kingdom UK Online

ITIL® Managing Across the Lifecycle is a higher level of qualification within the ITIL® certification scheme. The certification aids students in being able to demonstrate knowledge of the ITIL® scheme in its entirety. [+]

Top Online Courses in Business Information Technology. What are the objectives of this course? The ITIL Managing Across the Lifecycle course will help you to develop the skills you need to oversee the complete ITIL service lifecycle and deliver the projected benefits and improvements. Building a communications framework that keeps stakeholders engaged and informed throughout the ITIL lifecycle. Building robust processes to manage cases and issues across the entire service delivery framework. Using the framework to manage issues as they pass through each stage of the lifecycle. Arranging organisational structures to deliver high quality IT services and applying rules to ensure frameworks are adhered to. Putting the framework into operation and using measurement and assessment to implement a continuous improvement program that delivers a consistent, repeatable ROI. Who is it intended for? Anyone who has completed the ITIL® Intermediate Track, amassed the 17 credits of their choice and is interested in furthering their career within the IT service management field to achieve a well-rounded, superior knowledge of skills in ITIL®. Requirements In order to take the Managing Across the Lifecycle exam, you must have achieved 17 units from the Foundation stage and Intermediate stage courses that best suit your professional and personal development goals. What marks this course apart? Once the Managing Across the Lifecycle exam has been passed, you will be able to oversee the ITIL® lifecycle in its entirety. Roles that usually demand this include business change manager, IT director or service delivery manager. Upon completion of the ITIL® Expert you can go on to apply for the title of ITIL® Master. What happens after requesting information? Once you have enquired you will be contacted by one of our specialist careers advisors who will be able to provide you with any further information you require. [-]

ITIL® Expert Level - Managing across the Lifecycle (MALC) Training & Exam Package

E-Careers
Online Part time 12 months Open Enrollment United Kingdom UK Online

ITIL® Managing Across the Lifecycle is a higher level of qualification within the ITIL® certification scheme. The certification aids students in being able to demonstrate knowledge of the ITIL® scheme in its entirety. [+]

What are the objectives of this course? The ITIL® Managing Across the Lifecycle course will help you to develop the skills you need to oversee the complete ITIL® service lifecycle and deliver the projected benefits and improvements. Building a communications framework that keeps stakeholders engaged and informed throughout the ITIL® lifecycle. Building robust processes to manage cases and issues across the entire service delivery framework. Using the framework to manage issues as they pass through each stage of the lifecycle. Arranging organisational structures to deliver high quality IT services and applying rules to ensure frameworks are adhered to. Putting the framework into operation and using measurement and assessment to implement a continuous improvement program that delivers a consistent, repeatable ROI. Who is it intended for? Anyone who has completed the ITIL® Intermediate Track, amassed the 17 credits of their choice and is interested in furthering their career within the IT service management field to achieve a well-rounded, superior knowledge of skills in ITIL®. Requirements In order to take the Managing Across the Lifecycle exam, you must have achieved 17 units from the Foundation stage and Intermediate stage courses that best suit your professional and personal development goals. What marks this course apart? Once the Managing Across the Lifecycle exam has been passed, you will be able to oversee the ITIL® lifecycle in its entirety. Roles that usually demand this include business change manager, IT director or service delivery manager. Upon completion of the ITIL® Expert you can go on to apply for the title of ITIL® Master. What happens after requesting information? Once you have enquired you will be contacted by one of our specialist careers advisors who will be able to provide you with any further information you require. [-]

ITIL® Intermediate Level - Service Offerings & Agreements (SOA) Training & Exam Package

E-Careers
Online Part time 12 months Open Enrollment United Kingdom UK Online

Focus on the service offerings and agreements element of the ITIL® framework and get certified with this training and examination package. [+]

Top Online Courses in Business Information Technology. What are the objectives of this course? The ITIL® SOA course will introduce students to the concepts behind service offerings and service level agreements, before moving on to more detailed analysis of the procedures and actions. Capturing user needs and defining services to match. Tracking and publicising services on offer to users and stakeholders. Negotiating and defining Service Level Agreements and assigning roles and responsibilities to ensure they are maintained. Monitoring service usage and assigning resources as and when required to maintain SLAs. Integrating third parties into service provision and defining processes that maintain SLAs and service quality. Defining the business value of formalised IT operations and using insights gained for better budgeting. Collecting service user feedback and resolving complaints to raise satisfaction levels. Defining the human resources required to deliver services and assigning roles and duties to maintain standards. Specifying and implementing the technologies required to assist with service provision. Who is it intended for? The course will be of interest to IT operations managers, service desk managers and IT professionals who already hold the ITIL® Foundation Qualification. The course will help IT professionals to build and deploy service offerings and agreements that meet the needs of their service users without affecting other business goals. Requirements In order to take the Service Offerings and Agreement exam, you must have passed the ITIL® Foundation Examination. There are no pre-requisites to take the course but we recommend you have a good knowledge of service management and have taken the ITIL® Foundation course. What marks this course apart? Once the Service Offerings and Agreements exam has been passed you will be able to function as an IT Finance Manager, Business Continuity Manager or Service Portfolio Manager. The course counts as four of the necessary 17 credits to move onto Managing Across the Lifecycle course which leads to the title of “ITIL® Expert”. What happens after requesting information? Once you have enquired you will be contacted by one of our specialist careers advisors who will be able to provide you with any further information you require. [-]

Course - How to Make a Website

Treehouse
Online Full time Part time Open Enrollment USA USA Online

If you’ve never built a website before and you have no coding or design experience, this is the place to start. In this project, we learn how to build a modern portfolio website for desktops, tablets, and mobile devices. We start with basic HTML and CSS syntax. Next, we learn how to build custom web pages with an image gallery and contact page. Finally, we walk through how to share a website live on the web. [+]

How to Make a Website If you’ve never built a website before and you have no coding or design experience, this is the place to start. In this project, we learn how to build a modern portfolio website for desktops, tablets, and mobile devices. We start with basic HTML and CSS syntax. Next, we learn how to build custom web pages with an image gallery and contact page. Finally, we walk through how to share a website live on the web. What you'll learn How to write basic HTML How to style web pages with CSS How to purchase a domain and hosting How to upload files Beginning HTML and CSS In this quick tutorial, we’ll check out an example of the final web project we’re aiming to build. Then, we’ll learn how to code our first HTML element, which will help form the structure of our website. Finally, we’ll finish up by styling our website with some simple CSS. These two languages, HTML and CSS, form the basic building blocks of any web project. HTML First HTML is a special computer language that describes the structure of a document. With HTML, we can build web pages that contain text, images, and many other types of content. First, we’ll get started with a quick history lesson. Then we’ll dig into the latest advancements in HTML by creating a simple page structure. Creating HTML Content When building websites, it's best to write as much of the HTML structure as possible before moving on to CSS. In practice, you'll move back and forth between HTML and CSS, but building most of the structure first will make it an easier process. First we will start by creating the navigation for our site. Then, we can move on to structuring the image gallery and other page content. Finally, we'll finish by including a CSS file into our HTML page. CSS: Cascading Style Sheets CSS is a language that allows us to make designs that are well organized and beautiful. While HTML describes the structure of information, CSS describes how that information should be visually presented. Before we start coding the CSS for our site, we will spend some time learning about the syntax of CSS. Customizing Colors and Fonts Colors in CSS require a special coded format called hexadecimal. We will first learn about hexadecimal numbers and then we can use them in our color values. Then, we’ll learn how to find licensed fonts as well as how to include fonts in a webpage. Styling Web Pages and Navigation The techniques necessary for styling an image gallery as well as horizontal navigation are actually quite similar. First, we will learn how to style a group of images and convert them into rows and columns for our image gallery. Then, we will use a similar CSS technique to create horizontal navigation from an unordered list. Adding Pages to a Website When multiple web pages are linked together, the pages become collectively known as a website. The home page will serve as the template for both our contact page and about page. In both pages, we will learn some new CSS techniques. Responsive Web Design and Testing Modern websites are built with mobile and desktop users in mind. By building our site with fluid percentages (instead of fixed pixels), we’re off to a good start. However, we can add special CSS rules called media queries to further enhance the experience. After adding responsive design, we will test the site on a few devices. Sharing a Website We're finished coding our website and now it's time to deploy it live to the web so that other people can see it. First, we will purchase our domain and hosting. Then, we will use the File Transfer Protocol (FTP) to put our files onto our server. Debugging HTML and CSS Problems When creating websites, problem solving skills are essential. First, we will learn how to access the developer tools to find problems with our code. Then, we will walk through some common HTML and CSS issues and how to fix them quickly. Teacher Nick Pettit Nick is a teacher at Treehouse and an independent game developer. His Twitter handle is @nickrp. [-]

Course in Big Data (Beginner)

Coursera
Online Part time 7 months Open Enrollment USA USA Online

Drive better business decisions with an overview of how big data is organized, analyzed, and interpreted. Apply your insights to real-world problems and questions. [+]

Top Online Courses in Business Information Technology. Drive better business decisions with an overview of how big data is organized, analyzed, and interpreted. Apply your insights to real-world problems and questions. Do you need to understand big data and how it will impact your business? This Specialization is for you. You will gain an understanding of what insights big data can provide through hands-on experience with the tools and systems used by big data scientists and engineers. Previous programming experience is not required! You will be guided through the basics of using Hadoop with MapReduce, Spark, Pig and Hive. By following along with provided code, you will experience how one can perform predictive modeling and leverage graph analytics to model problems. This specialization will prepare you to ask the right questions about data, communicate effectively with data scientists, and do basic exploration of large, complex datasets. In the final Capstone Project, developed in partnership with data software company Splunk, you’ll apply the skills you learned to do basic analyses of big data. Courses Introduction to Big Data Interested in increasing your knowledge of the Big Data landscape? This course is for those new to data science and interested in understanding why the Big Data Era has come to be. It is for those who want to become conversant with the terminology and the core concepts behind big data problems, applications, and systems. It is for those who want to start thinking about how Big Data might be useful in their business or career. It provides an introduction to one of the most common frameworks, Hadoop, that has made big data analysis easier and more accessible -- increasing the potential for data to transform our world! At the end of this course, you will be able to: - Describe the Big Data landscape including examples of real world big data problems including the three key sources of Big Data: people, organizations, and sensors. - Explain the V’s of Big Data (volume, velocity, variety, veracity, valence, and value) and why each impacts data collection, monitoring, storage, analysis and reporting. - Get value out of Big Data by using a 5-step process to structure your analysis. - Identify what are and what are not big data problems and be able to recast big data problems as data science questions. - Provide an explanation of the architectural components and programming models used for scalable big data analysis. - Summarize the features and value of core Hadoop stack components including the YARN resource and job management system, the HDFS file system and the MapReduce programming model. - Install and run a program using Hadoop! This course is for those new to data science. No prior programming experience is needed, although the ability to install applications and utilize a virtual machine is necessary to complete the hands-on assignments. Hardware Requirements: (A) Quad Core Processor (VT-x or AMD-V support recommended), 64-bit; (B) 8 GB RAM; (C) 20 GB disk free. How to find your hardware information: (Windows): Open System by clicking the Start button, right-clicking Computer, and then clicking Properties; (Mac): Open Overview by clicking on the Apple menu and clicking “About This Mac.” Most computers with 8 GB RAM purchased in the last 3 years will meet the minimum requirements.You will need a high speed internet connection because you will be downloading files up to 4 Gb in size. Software Requirements: This course relies on several open-source software tools, including Apache Hadoop. All required software can be downloaded and installed free of charge. Software requirements include: Windows 7+, Mac OS X 10.10+, Ubuntu 14.04+ or CentOS 6+ VirtualBox 5+. Big Data Modeling and Management Systems Once you’ve identified a big data issue to analyze, how do you collect, store and organize your data using Big Data solutions? In this course, you will experience various data genres and management tools appropriate for each. You will be able to describe the reasons behind the evolving plethora of new big data platforms from the perspective of big data management systems and analytical tools. Through guided hands-on tutorials, you will become familiar with techniques using real-time and semi-structured data examples. Systems and tools discussed include: AsterixDB, HP Vertica, Impala, Neo4j, Redis, SparkSQL. This course provides techniques to extract value from existing untapped data sources and discovering new data sources. At the end of this course, you will be able to: - Recognize different data elements in your own work and in everyday life problems - Explain why your team needs to design a Big Data Infrastructure Plan and Information System Design - Identify the frequent data operations required for various types of data - Select a data model to suit the characteristics of your data - Apply techniques to handle streaming data - Differentiate between a traditional Database Management System and a Big Data Management System - Appreciate why there are so many data management systems - Design a big data information system for an online game company This course is for those new to data science. Completion of Intro to Big Data is recommended. No prior programming experience is needed, although the ability to install applications and utilize a virtual machine is necessary to complete the hands-on assignments. Refer to the specialization technical requirements for complete hardware and software specifications. Hardware Requirements: (A) Quad Core Processor (VT-x or AMD-V support recommended), 64-bit; (B) 8 GB RAM; (C) 20 GB disk free. How to find your hardware information: (Windows): Open System by clicking the Start button, right-clicking Computer, and then clicking Properties; (Mac): Open Overview by clicking on the Apple menu and clicking “About This Mac.” Most computers with 8 GB RAM purchased in the last 3 years will meet the minimum requirements.You will need a high speed internet connection because you will be downloading files up to 4 Gb in size. Software Requirements: This course relies on several open-source software tools, including Apache Hadoop. All required software can be downloaded and installed free of charge (except for data charges from your internet provider). Software requirements include: Windows 7+, Mac OS X 10.10+, Ubuntu 14.04+ or CentOS 6+ VirtualBox 5+. Big Data Integration and Processing At the end of the course, you will be able to: - Retrieve data from example database and big data management systems - Describe the connections between data management operations and the big data processing patterns needed to utilize them in large-scale analytical applications - Identify when a big data problem needs data integration - Execute simple big data integration and processing on Hadoop and Spark platforms This course is for those new to data science. Completion of Intro to Big Data is recommended. No prior programming experience is needed, although the ability to install applications and utilize a virtual machine is necessary to complete the hands-on assignments. Refer to the specialization technical requirements for complete hardware and software specifications. Hardware Requirements: (A) Quad Core Processor (VT-x or AMD-V support recommended), 64-bit; (B) 8 GB RAM; (C) 20 GB disk free. How to find your hardware information: (Windows): Open System by clicking the Start button, right-clicking Computer, and then clicking Properties; (Mac): Open Overview by clicking on the Apple menu and clicking “About This Mac.” Most computers with 8 GB RAM purchased in the last 3 years will meet the minimum requirements.You will need a high speed internet connection because you will be downloading files up to 4 Gb in size. Software Requirements: This course relies on several open-source software tools, including Apache Hadoop. All required software can be downloaded and installed free of charge (except for data charges from your internet provider). Software requirements include: Windows 7+, Mac OS X 10.10+, Ubuntu 14.04+ or CentOS 6+ VirtualBox 5+. Machine Learning With Big Data Want to make sense of the volumes of data you have collected? Need to incorporate data-driven decisions into your process? This course provides an overview of machine learning techniques to explore, analyze, and leverage data. You will be introduced to tools and algorithms you can use to create machine learning models that learn from data, and to scale those models up to big data problems. At the end of the course, you will be able to: - Design an approach to leverage data using the steps in the machine learning process. - Apply machine learning techniques to explore and prepare data for modeling. - Identify the type of machine learning problem in order to apply the appropriate set of techniques. - Construct models that learn from data using widely available open source tools. - Analyze big data problems using scalable machine learning algorithms on Spark. Graph Analytics for Big Data Want to understand your data network structure and how it changes under different conditions? Curious to know how to identify closely interacting clusters within a graph? Have you heard of the fast-growing area of graph analytics and want to learn more? This course gives you a broad overview of the field of graph analytics so you can learn new ways to model, store, retrieve and analyze graph-structured data. After completing this course, you will be able to model a problem into a graph database and perform analytical tasks over the graph in a scalable manner. Better yet, you will be able to apply these techniques to understand the significance of your data sets for your own projects. Big Data - Capstone Project Welcome to the Capstone Project for Big Data! In this culminating project, you will build a big data ecosystem using tools and methods form the earlier courses in this specialization. You will analyze a data set simulating big data generated from a large number of users who are playing our imaginary game "Catch the Pink Flamingo". During the five week Capstone Project, you will walk through the typical big data science steps for acquiring, exploring, preparing, analyzing, and reporting. In the first two weeks, we will introduce you to the data set and guide you through some exploratory analysis using tools such as Splunk and Open Office. Then we will move into more challenging big data problems requiring the more advanced tools you have learned including KNIME, Spark's MLLib and Gephi. Finally, during the fifth and final week, we will show you how to bring it all together to create engaging and compelling reports and slide presentations. As a result of our collaboration with Splunk, a software company focus on analyzing machine-generated big data, learners with the top projects will be eligible to present to Splunk and meet Splunk recruiters and engineering leadership. [-]

Course in Big Data (2015) (Beginner)

Coursera
Online Part time 7 months Open Enrollment USA USA Online

Do you need to understand big data and how it will impact your business? This Specialization is for you. You will gain an understanding of what insights big data can provide through hands-on experience with the tools and systems used by big data scientists and engineers. Previous programming experience is not required! [+]

Drive better business decisions with an overview of how big data is organized, analyzed, and interpreted. Apply your insights to real-world problems and questions. Do you need to understand big data and how it will impact your business? This Specialization is for you. You will gain an understanding of what insights big data can provide through hands-on experience with the tools and systems used by big data scientists and engineers. Previous programming experience is not required! You will be guided through the basics of using Hadoop with MapReduce, Spark, Pig and Hive. By following along with provided code, you will experience how one can perform predictive modeling and leverage graph analytics to model problems. This specialization will prepare you to ask the right questions about data, communicate effectively with data scientists, and do basic exploration of large, complex datasets. In the final Capstone Project, developed in partnership with data software company Splunk, you’ll apply the skills you learned to do basic analyses of big data. Courses Introduction to Big Data Interested in increasing your knowledge of the Big Data landscape? This course is for those new to data science and interested in understanding why the Big Data Era has come to be. It is for those who want to become conversant with the terminology and the core concepts behind big data problems, applications, and systems. It is for those who want to start thinking about how Big Data might be useful in their business or career. It provides an introduction to one of the most common frameworks, Hadoop, that has made big data analysis easier and more accessible -- increasing the potential for data to transform our world! At the end of this course, you will be able to: - Describe the Big Data landscape including examples of real world big data problems including the three key sources of Big Data: people, organizations, and sensors. - Explain the V’s of Big Data (volume, velocity, variety, veracity, valence, and value) and why each impacts data collection, monitoring, storage, analysis and reporting. - Get value out of Big Data by using a 5-step process to structure your analysis. - Identify what are and what are not big data problems and be able to recast big data problems as data science questions. - Provide an explanation of the architectural components and programming models used for scalable big data analysis. - Summarize the features and value of core Hadoop stack components including the YARN resource and job management system, the HDFS file system and the MapReduce programming model. - Install and run a program using Hadoop! This course is for those new to data science. No prior programming experience is needed, although the ability to install applications and utilize a virtual machine is necessary to complete the hands-on assignments. Hardware Requirements: (A) Quad Core Processor (VT-x or AMD-V support recommended), 64-bit; (B) 8 GB RAM; (C) 20 GB disk free. How to find your hardware information: (Windows): Open System by clicking the Start button, right-clicking Computer, and then clicking Properties; (Mac): Open Overview by clicking on the Apple menu and clicking “About This Mac.” Most computers with 8 GB RAM purchased in the last 3 years will meet the minimum requirements.You will need a high speed internet connection because you will be downloading files up to 4 Gb in size. Software Requirements: This course relies on several open-source software tools, including Apache Hadoop. All required software can be downloaded and installed free of charge. Software requirements include: Windows 7+, Mac OS X 10.10+, Ubuntu 14.04+ or CentOS 6+ VirtualBox 5+. Big Data Modeling and Management Systems Once you’ve identified a big data issue to analyze, how do you collect, store and organize your data using Big Data solutions? In this course, you will experience various data genres and management tools appropriate for each. You will be able to describe the reasons behind the evolving plethora of new big data platforms from the perspective of big data management systems and analytical tools. Through guided hands-on tutorials, you will become familiar with techniques using real-time and semi-structured data examples. Systems and tools discussed include: AsterixDB, HP Vertica, Impala, Neo4j, Redis, SparkSQL. This course provides techniques to extract value from existing untapped data sources and discovering new data sources. At the end of this course, you will be able to: - Recognize different data elements in your own work and in everyday life problems - Explain why your team needs to design a Big Data Infrastructure Plan and Information System Design - Identify the frequent data operations required for various types of data - Select a data model to suit the characteristics of your data - Apply techniques to handle streaming data - Differentiate between a traditional Database Management System and a Big Data Management System - Appreciate why there are so many data management systems - Design a big data information system for an online game company This course is for those new to data science. Completion of Intro to Big Data is recommended. No prior programming experience is needed, although the ability to install applications and utilize a virtual machine is necessary to complete the hands-on assignments. Refer to the specialization technical requirements for complete hardware and software specifications. Hardware Requirements: (A) Quad Core Processor (VT-x or AMD-V support recommended), 64-bit; (B) 8 GB RAM; (C) 20 GB disk free. How to find your hardware information: (Windows): Open System by clicking the Start button, right-clicking Computer, and then clicking Properties; (Mac): Open Overview by clicking on the Apple menu and clicking “About This Mac.” Most computers with 8 GB RAM purchased in the last 3 years will meet the minimum requirements.You will need a high speed internet connection because you will be downloading files up to 4 Gb in size. Software Requirements: This course relies on several open-source software tools, including Apache Hadoop. All required software can be downloaded and installed free of charge (except for data charges from your internet provider). Software requirements include: Windows 7+, Mac OS X 10.10+, Ubuntu 14.04+ or CentOS 6+ VirtualBox 5+. Big Data Integration and Processing At the end of the course, you will be able to: - Retrieve data from example database and big data management systems - Describe the connections between data management operations and the big data processing patterns needed to utilize them in large-scale analytical applications - Identify when a big data problem needs data integration - Execute simple big data integration and processing on Hadoop and Spark platforms This course is for those new to data science. Completion of Intro to Big Data is recommended. No prior programming experience is needed, although the ability to install applications and utilize a virtual machine is necessary to complete the hands-on assignments. Refer to the specialization technical requirements for complete hardware and software specifications. Hardware Requirements: (A) Quad Core Processor (VT-x or AMD-V support recommended), 64-bit; (B) 8 GB RAM; (C) 20 GB disk free. How to find your hardware information: (Windows): Open System by clicking the Start button, right-clicking Computer, and then clicking Properties; (Mac): Open Overview by clicking on the Apple menu and clicking “About This Mac.” Most computers with 8 GB RAM purchased in the last 3 years will meet the minimum requirements.You will need a high speed internet connection because you will be downloading files up to 4 Gb in size. Software Requirements: This course relies on several open-source software tools, including Apache Hadoop. All required software can be downloaded and installed free of charge (except for data charges from your internet provider). Software requirements include: Windows 7+, Mac OS X 10.10+, Ubuntu 14.04+ or CentOS 6+ VirtualBox 5+. Machine Learning With Big Data Want to make sense of the volumes of data you have collected? Need to incorporate data-driven decisions into your process? This course provides an overview of machine learning techniques to explore, analyze, and leverage data. You will be introduced to tools and algorithms you can use to create machine learning models that learn from data, and to scale those models up to big data problems. At the end of the course, you will be able to: - Design an approach to leverage data using the steps in the machine learning process. - Apply machine learning techniques to explore and prepare data for modeling. - Identify the type of machine learning problem in order to apply the appropriate set of techniques. - Construct models that learn from data using widely available open source tools. - Analyze big data problems using scalable machine learning algorithms on Spark. Graph Analytics for Big Data Want to understand your data network structure and how it changes under different conditions? Curious to know how to identify closely interacting clusters within a graph? Have you heard of the fast-growing area of graph analytics and want to learn more? This course gives you a broad overview of the field of graph analytics so you can learn new ways to model, store, retrieve and analyze graph-structured data. After completing this course, you will be able to model a problem into a graph database and perform analytical tasks over the graph in a scalable manner. Better yet, you will be able to apply these techniques to understand the significance of your data sets for your own projects. Big Data - Capstone Project Welcome to the Capstone Project for Big Data! In this culminating project, you will build a big data ecosystem using tools and methods form the earlier courses in this specialization. You will analyze a data set simulating big data generated from a large number of users who are playing our imaginary game "Catch the Pink Flamingo". During the five week Capstone Project, you will walk through the typical big data science steps for acquiring, exploring, preparing, analyzing, and reporting. In the first two weeks, we will introduce you to the data set and guide you through some exploratory analysis using tools such as Splunk and Open Office. Then we will move into more challenging big data problems requiring the more advanced tools you have learned including KNIME, Spark's MLLib and Gephi. Finally, during the fifth and final week, we will show you how to bring it all together to create engaging and compelling reports and slide presentations. As a result of our collaboration with Splunk, a software company focus on analyzing machine-generated big data, learners with the top projects will be eligible to present to Splunk and meet Splunk recruiters and engineering leadership. [-]

CompTIA Cloud Essentials (CLO-001)

E-Careers
Online Part time Open Enrollment United Kingdom UK Online

Seek opportunities in the exciting and expanding IT industry in one of the most specialised areas. Ensure that you have the relevant knowledge of cloud computing and its key concepts with this CompTIA Cloud Essentials course. [+]

Top Online Courses in Business Information Technology. What are the objectives of this course? This course will teach students the essential knowledge needed to understand cloud computing and its basic concepts. Characteristics of cloud services from a business perspective Business value of cloud computing Technical perspective/cloud types Steps to successful adoption Impact and changes on IT service management Risks and consequences Who is it intended for? Anyone who is looking to gain the fundamental and practical knowledge of cloud computing, whether that be IT professionals or non-IT staff. Requirements There are no pre-requisites for this course. What marks this course apart? Once students have completed this course they can go on to study further cloud-based qualifications or look to tie it in with other courses to provide a broader IT knowledge base. Students will be able to function in roles such as cloud engineer, cloud systems engineer and cloud support engineer. What happens after requesting information? Once you have enquired you will be contacted by one of our specialist careers advisors who will be able to provide you with any further information you require. [-]

IT Project Manager Certification (PRINCE2 Foundation & Practitioner, Mentor+, ITIL Foundation & Exams)

E-Careers
Online Part time 12 months Open Enrollment United Kingdom UK Online

Gain expertise in both the PRINCE2® and ITIL® frameworks and become fully certified with an official licensed affiliate with this two course package. [+]

What are the objectives of this course? Be able to lead a team of testers, developer, analysts and engineers professionally and effectively with these world-renowned frameworks and achieve full certification. PRINCE2® Our PRINCE2® course comes including the full syllabus from Axelos, as well as both official examinations for you to achieve Practitioner status: Getting started & Introduction to PRINCE2® Processes SU and IP Processes CS and MP Processes DP, SB & CP Organisation Theme Business Case Theme Risk Theme Plans Theme Quality Theme Change Theme Progress Theme Exam Preparation and Approaches ITIL® Foundation Our ITIL® Foundation course provides you with the full training syllabus concerning the ITIL® framework and how to apply it. The official examination is also included for full certification: The service management lifecycle and the key stages used to manage service requests. Defining a service strategy that meets the needs of all users of the IT service. Implementing a service that supports the strategy. Building intermediate delivery services that maintain standards during the transition period. The operations required to maintain customers expected levels of service and satisfaction. Building a continual service improvement plan that keeps raising standards and customer satisfaction levels. Who is it intended for? This package is perfect for anyone who is looking to gain industry-recognised qualifications as an attempt to either break into, or work your way up in the project management industry. Requirements There are no prerequisites for this package. What marks this course apart? As the name of this package suggests you will be able to become a project manager that specialises in IT, however due to the flexibility of both methodologies you will not be limited to IT and can apply them into any industry. What happens after requesting information? Once you have enquired you will be contacted by one of our specialist careers advisors who will be able to provide you with any further information you require. [-]

Course - PHP Basics

Treehouse
Online Full time Part time Open Enrollment USA USA Online

In this course I'll walk you through the basics of the language, ranging from basic statements to conditionals. We'll be creating a simple "Unit Converter" as well as a "Daily Exercise Program". We'll then finish up by combining those programs with HTML to create a personal webpage to demonstrate your skills. [+]

Top Online Courses in Business Information Technology. PHP Basics In this course I'll walk you through the basics of the language, ranging from basic statements to conditionals. We'll be creating a simple "Unit Converter" as well as a "Daily Exercise Program". We'll then finish up by combining those programs with HTML to create a personal webpage to demonstrate your skills. What you'll learn Variables Operators Conditionals Comments PHP on the Web Getting to Know PHP PHP is one of the most widely used technologies on the internet today, supporting many large projects such as WordPress, Drupal, Wikipedia and Facebook. A conservative estimate is that 25% of the web is built on PHP. The driving force behind PHP has always been; to solve problems, and make it faster and easier to build web sites. Because of this drive, PHP is a great choice for creating simple yet powerful web sites and applications. Unit Converter PHP has 2 types of number variables: integers, for whole numbers such as 1 though 9, and floats, for fractions such as the cost of 1.99. In this course we'll be creating a simple unit converter which will use these number variables, along with arithmetic operators, to calculate weight and distance conversions. Daily Exercise Program In this section, we'll continue to expand upon the skills you've learned, as we explore more data types and the logic needed to create a "Daily Exercise Program". We'll store each exercise in a STRING variable, then we'll use conditionals to control which exercise is displayed. PHP on the Web In this section, we'll use PHP in combination with HTML to create your first PHP webpage. You'll learn how PHP can reduce busy work and maintenance, allowing us to work faster and be more productive. Finally we'll combine the previous scripts to create a personal webpage to demonstrate your skills. Teacher Alena Holligan After starting out in fine art and moving into graphic design, Alena found her passion for programming over 15 years ago and has never looked back. Alena enjoys community and is excited to introduce people to the wonderful world of PHP and the Portland Tech Community. When not at her computer, Alena enjoys exploring Portland with her friends and family, including her 3 young children. She also enjoys the Symphony, Cooking, Books, Yarn and Yoga. [-]