Online Course in IT

Best Online Courses in IT 2017

IT

An online course is a web-based learning experience in which students log on and engage in traditional class activities such as reading, discussion and testing. The online format allows for completion of coursework on each student’s schedule, but engagement and collaboration are still fostered in the online classroom.

What is an online course in IT? Information technology, or IT for short, is the catchall phrase that refers to the systems, hardware, software and network applications that work to manage and communicate information used by companies and individuals. You will study these aspects of IT with the goal of understanding how information is handled, what common problems occur throughout this process and what methods are commonly used to mitigate complications. Students should emerge with a solid understanding of IT’s essential principles as well as the problem-solving methods that should be applied.

This online course can benefit students by acquainting them with the foundation of the information technology sector, but more importantly, by imparting the analytical skills necessary to find solutions to problems. The latter of these skills are sure to be an asset in nearly any position or situation.

You can get more information on the expenses of an online course in IT by contacting the admissions office where you plan to attend. A representative will calculate your applicable costs.

IT is recognized as one of the most rapidly growing fields, so of course, there won’t likely be a shortage of jobs to pursue with your newfound IT expertise. You can qualify yourself further by completing your degree program, too. Some of the positions you may be qualified for include IT specialist, network engineer, technical support personnel or web developer. With such a range of options, it’s no wonder this degree is such a popular option.

You may be able to enroll in an online course in IT through your own university. 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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Course in Data Warehousing for Business Intelligence (Advanced)

Coursera
Online Part time 5 months Open Enrollment USA USA Online

This Specialization covers data architecture skills that are increasingly critical across a broad range of technology fields. You’ll learn the basics of structured data modeling, gain practical SQL coding experience, and develop an in-depth understanding of data warehouse design and data manipulation. [+]

Top Online Courses in IT. Evaluate business needs, design a data warehouse, and integrate and visualize data using dashboards and visual analytics. This Specialization covers data architecture skills that are increasingly critical across a broad range of technology fields. You’ll learn the basics of structured data modeling, gain practical SQL coding experience, and develop an in-depth understanding of data warehouse design and data manipulation. You’ll have the opportunity to work with large data sets in a data warehouse environment to create dashboards and Visual Analytics. You will use of MicroStrategy, a leading BI tool, OLAP (online analytical processing) and Visual Insights capabilities to create dashboards and Visual Analytics. In the final Capstone Project, you’ll apply your skills to build a small, basic data warehouse, populate it with data, and create dashboards and other visualizations to analyze and communicate the data to a broad audience. Courses Database Management Essentials Database Management Essentials provides the foundation you need for a career in database development, data warehousing, or business intelligence, as well as for the entire Data Warehousing for Business Intelligence specialization. In this course, you will create relational databases, write SQL statements to extract information to satisfy business reporting requests, create entity relationship diagrams (ERDs) to design databases, and analyze table designs for excessive redundancy. As you develop these skills, you will use either Oracle or MySQL to execute SQL statements and a database diagramming tool such as the ER Assistant to create ERDs. We’ve designed this course to ensure a common foundation for specialization learners. Everyone taking the course can jump right in with writing SQL statements in Oracle or MySQL. Data Warehouse Concepts, Design, and Data Integration This is the second course in the Data Warehousing for Business Intelligence specialization. Ideally, the courses should be taken in sequence. In this course, you will learn exciting concepts and skills for designing data warehouses and creating data integration workflows. These are fundamental skills for data warehouse developers and administrators. You will have hands-on experience for data warehouse design and use open source products for manipulating pivot tables and creating data integration workflows.You will also gain conceptual background about maturity models, architectures, multidimensional models, and management practices, providing an organizational perspective about data warehouse development. If you are currently a business or information technology professional and want to become a data warehouse designer or administrator, this course will give you the knowledge and skills to do that. By the end of the course, you will have the design experience, software background, and organizational context that prepares you to succeed with data warehouse development projects. In this course, you will create data warehouse designs and data integration workflows that satisfy the business intelligence needs of organizations. When you’re done with this course, you’ll be able to: - Evaluate an organization for data warehouse maturity and business architecture alignment; - Create a data warehouse design and reflect on alternative design methodologies and design goals; - Create data integration workflows using prominent open source software; - Reflect on the role of change data, refresh constraints, refresh frequency trade-offs, and data quality goals in data integration process design; and - Perform operations on pivot tables to satisfy typical business analysis requests using prominent open source software Relational Database Support for Data Warehouses Relational Database Support for Data Warehouses is the third course in the Data Warehousing for Business Intelligence specialization. In this course, you'll use analytical elements of SQL for answering business intelligence questions. You'll learn features of relational database management systems for managing summary data commonly used in business intelligence reporting. Because of the importance and difficulty of managing implementations of data warehouses, we'll also delve into storage architectures, scalable parallel processing, data governance, and big data impacts. Business Intelligence Concepts, Tools, and Applications This is the fourth course in the Data Warehouse for Business Intelligence specialization. Ideally, the courses should be taken in sequence. In this course, you will gain the knowledge and skills for using data warehouses for business intelligence purposes and for working as a business intelligence developer. You’ll have the opportunity to work with large data sets in a data warehouse environment and will learn the use of MicroStrategy's Online Analytical Processing (OLAP) and Visualization capabilities to create visualizations and dashboards. The course gives an overview of how business intelligence technologies can support decision making across any number of business sectors. These technologies have had a profound impact on corporate strategy, performance, and competitiveness and broadly encompass decision support systems, business intelligence systems, and visual analytics. Modules are organized around the business intelligence concepts, tools, and applications, and the use of data warehouse for business reporting and online analytical processing, for creating visualizations and dashboards, and for business performance management and descriptive analytics. Design and Build a Data Warehouse for Business Intelligence Implementation The capstone course, Design and Build a Data Warehouse for Business Intelligence Implementation, features a real-world case study that integrates your learning across all courses in the specialization. In response to business requirements presented in a case study, you’ll design and build a small data warehouse, create data integration workflows to refresh the warehouse, write SQL statements to support analytical and summary query requirements, and use the MicroStrategy business intelligence platform to create dashboards and visualizations. In the first part of the capstone course, you’ll be introduced to a medium-sized firm, learning about their data warehouse and business intelligence requirements and existing data sources. You’ll first architect a warehouse schema and dimensional model for a small data warehouse. You’ll then create data integration workflows using Pentaho Data Integration to refresh your data warehouse. Next, you’ll write SQL statements for analytical query requirements and create materialized views to support summary data management. Finally, you will use MicroStrategy OLAP capabilities to gain insights into your data warehouse. In the completed project, you’ll have built a small data warehouse containing a schema design, data integration workflows, analytical queries, materialized views, dashboards and visualizations that you’ll be proud to show to your current and prospective employers. [-]

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. [+]

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." [-]

Data Protection in the Workplace - Certified

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

If you or your organisation handles personal information about individuals you have legal obligations to protect that information. The benefits of good data safety are numerous and include, good business practice, the protection of people’s rights and the protection of your organisations reputation. [+]

Apply Now - Special Offer

If you or your organisation handles personal information about individuals you have legal obligations to protect that information. The benefits of good data safety are numerous and include, good business practice, the protection of people’s rights and the protection of your organisations reputation. In recent years some companies and individuals have experienced serious legal consequences for data protection breaches and this highlights why it is so important to get it right. Training should be a vital part of any company’s data protection policy. What you will Learn / Course Modules Benefits of Good Data Safety Rights and Conditions The Data Protection Act Data Sharing and Security Creating a Data Protection Policy Putting it into Practice Handling the Requests for Personal Data [-]

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) [-]

Course: Big Data Analytics - Data Executive

361 Degree Minds
Online Full time 40 hours July 2017 India India Online

Big Data is about the tremendous amount of data being generated in this data-driven world. Whatever we do in this world leaves a digital trace. Big Data has become a very vital element for business growth and innovation that relies on technologies such as Internet of Things and Data Analytics. [+]

Top Online Courses in IT. Course: Big Data Analytics - Data Executive Big Data is about the tremendous amount of data being generated in this data-driven world. Whatever we do in this world leaves a digital trace. Big Data has become a very vital element for business growth and innovation that relies on technologies such as Internet of Things and Data Analytics. Big Data will revolutionize the operations of any organizations, just like how the internet did. Do you want to be part of the revolution? Are you cut out for Big Data? Big Data is the IT mega trend that will define this decade…Why? Data is only as useful as the individual interpreting it, who can translate the findings from data into actionable insights. People with Big Data Analytics skills are in demand. Many companies do not have employees who can interpret data - find the trends, patterns and stories. These insights drive the decision making in every company. Join the Data Executive course of 361DM to know how Big Data Analytics can be a world of opportunities. Are you ready for the Big Data Era? Wondering if Big Data Analytics is the right career for you? Are you confused if Big Data Analytics is the right choice? Take up the Data Executive, an entry level program to create a basic awareness on the concept of Big Data and Analytics. This will help you make self assessment and know if Big Data Analytics can complement your existing skill set. How Will Big Data Analytics shape up the future of the business world? Buying and selling data will become the new business for every organization. They will monetize the data by selling them either as unstructured data or value added data. IoT – Internet of things, an extension of Big Data Anlytics will be the next critical focus in coming years.The Internet of Things (IoT) is a network of physical objects that can be accessed via the Internet. The IoT focuses on the data generation and production. Machine learning will become the top strategic trend in the years to come. Machine learning will be a necessary aspect for data preparation and predictive analysis in businesses in the future. Big Data industry will face huge shortage of experts like data analysts, data engineers and experts in Data Management according to IDC. Why 361DM is the best choice for your learning on Big Data Analytics? 361DM has been in the field of Leadership & Organizational Development for 17 years offering programs on Big Data Analytics, designed by industry veterans. The Data Executive program is industry relevant and crafted by Big Data Analytics Industry veteran, Mr. Suresh Krishnaswamy who has developed similar programmes for IIT and Great Lakes. He has worked with companies Like IBM, EDS & Cognizant. The clients include Cognizant, Nokia Siemens, Sandisk, Manhattan Associates, etc. 361DM experts focus on upskilling thereby providing one-on-one assistance to help you identify your target jobs, spruce up your resume and prep for the analytics interview. Program Suggestion Program Name: Data Executive Program designed for: For beginners to Create Awareness on Big Data Eligibility: Any UG/ PG Graduates Eligibility Process: NA Duration: 40 Hours Fees: 110 USD Installment pattern available (Y/N): No Program Outcome: This is an entry level program designed for beginners to create awareness about Big Data. It introduces learners to concepts like Big Data 1O1, Mathematics Modeling, Coding in DB Environment and Coding in DB Environment. [-]

Course in Cybersecurity (Intermediate)

Coursera
Online Part time Open Enrollment USA USA Online

The Cybersecurity Specialization covers the fundamental concepts underlying the construction of secure systems, from the hardware to the software to the human-computer interface, with the use of cryptography to secure interactions. [+]

The Cybersecurity Specialization covers the fundamental concepts underlying the construction of secure systems, from the hardware to the software to the human-computer interface, with the use of cryptography to secure interactions. These concepts are illustrated with examples drawn from modern practice, and augmented with hands-on exercises involving relevant tools and techniques. Successful participants will develop a way of thinking that is security-oriented, better understanding how to think about adversaries and how to build systems that defend against them. Courses Usable Security This course focuses on how to design and build secure systems with a human-centric focus. We will look at basic principles of human-computer interaction, and apply these insights to the design of secure systems with the goal of developing security measures that respect human performance and their goals within a system. Software Security This course we will explore the foundations of software security. We will consider important software vulnerabilities and attacks that exploit them -- such as buffer overflows, SQL injection, and session hijacking -- and we will consider defenses that prevent or mitigate these attacks, including advanced testing and program analysis techniques. Importantly, we take a "build security in" mentality, considering techniques at each phase of the development cycle that can be used to strengthen the security of software systems. Cryptography This course will introduce you to the foundations of modern cryptography, with an eye toward practical applications. Hardware Security In this course, we will study security and trust from the hardware perspective. Upon completing the course, students will understand the vulnerabilities in current digital system design flow and the physical attacks to these systems. They will learn that security starts from hardware design and be familiar with the tools and skills to build secure and trusted hardware. Cybersecurity Capstone Project This course presents an intensive experience during which students build a software system they intend to be secure, and then attempt to show that other students' projects are insecure, by finding flaws in them. [-]

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 IT. 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. [-]

Data Protection in the Workplace - Certified

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

If you or your organisation handles personal information about individuals you have legal obligations to protect that information. The benefits of good data safety are numerous and include, good business practice, the protection of people’s rights and the protection of your organisations reputation. [+]

Apply Now - Special Offer

If you or your organisation handles personal information about individuals you have legal obligations to protect that information. The benefits of good data safety are numerous and include, good business practice, the protection of people’s rights and the protection of your organisations reputation. In recent years some companies and individuals have experienced serious legal consequences for data protection breaches and this highlights why it is so important to get it right. Training should be a vital part of any company’s data protection policy. What you will Learn / Course Modules Benefits of Good Data Safety Rights and Conditions The Data Protection Act Data Sharing and Security Creating a Data Protection Policy Putting it into Practice Handling the Requests for Personal Data [-]

Course: Big Data Analytics - Business Analyst

361 Degree Minds
Online Full time 232 hours July 2017 India India Online

Are you looking to build a career in Big Data Analytics? Every professional working in the corporate environment must think of their way to the next position. If you are interested in Big Data Analytics then you must retool your skills to be a part of the Big Data space. [+]

Course: Big Data Analytics - Business Analyst Career transition to Big Data Analytics: Are you looking to build a career in Big Data Analytics? Every professional working in the corporate environment must think of their way to the next position. If you are interested in Big Data Analytics then you must retool your skills to be a part of the Big Data space. This industry requires some basic qualities like a strong grounding in mathematics, familiarity with programming languages, understanding the logic of analytical modelling, content knowledge and above all an inherent sense of curiosity. 361DM career transition programs are designed to identify the skills you need to transition to an analytics career. Get trained by industry thought leaders in Big Data Analytics with focus on solving real corporate problems. Interested in Transformation to Big Data Analytics Career Path? Do you want a role which requires you to derive insights from data? Do you like to find a story in data? 361DM Big Data Analytics course are crafted to identify the skills in you to transform you into Big Data Analytics professional. According to Forbes, Big Data is becoming a movement. Every enterprise is going to take the advantage of Big Data Analytics. According to IDC, the Big Data market is predicted to be worth $46.34 billion by 2018. The global Hadoop market is forecast to grow at a CAGR of 59.37% during the period 2016-2020, according to Business Wire. Hadoop, a cost effective technology is faster than the conventional data analysis tools such as Relational Database Management Systems (RDBMS). R, the open source statistical software is used to tackle problems in data analysis. The data analysis is done using statistical concepts and mathematical modelling. With 361DM learn to implement Big Data Analytics to products, operations, marketing and consumer experience problems in industries like in retail, automobile, banking & financial services and healthcare. The path to Big Data Analytics......What it takes to be ‘The’ professional? Now, you know why Big Data Analytics is a good career transition. But before you go too far, make sure you have the required skills in you. Are you analytical in nature? Are you a problem solver? Make sure you have the basic quality of thinking analytically. 361DM offers Data Executive course to give you an idea of the skills required for Big Data Analytics. Some professionals try to enter into a new industry when they make the transition into the analytics. This move will reduce the chances of you finding a job. Look for an analyst job in the industry you have experience in. Once you are placed in an analytics role successfully and after gaining experience, you can think of moving to the industry you want to be in. Leaving your current job to make the career transition is not the right option, as finding a new job can take time and adding pressure on you unnecessarily. 361DM training programs offers the convenience of ‘Anytime Anywhere’ & disruptive value proposition to the corporate workforce. Do you want a career transition for an attractive paycheck? Big Data Analytics is the answer. In this information age, the technology to store data is increasing exponentially. Every company needs to make decisions from data. These decisions determine a company’s existence. Those who can control access to data, understand data and interpret data will have an edge in the near future, thereby leading to better paychecks. The demand for Big Data Analytics professional is high at the moment. The difficulty in finding the data scientist is growing up from 79% to 83% according to CrowdFlower survey. Companies are willing to shell out big bucks to find a person with adequate knowledge in Big Data skills. Thanks to the shortage of Big Data professionals. With the right mix of technical skills and personal skills, you will be the sought after Big Data professional. 361DM has cutting edge courses created by industry thought leaders to get you your dream job. Why 361 Degree Minds? 361 Degree Minds, a premier career building institute led by team of BITS Alumni with in-depth domain knowledge. Our courses are industry relevant and crafted by Big Data Analytics Industry veteran, Mr. Suresh Krishnaswamy who has developed similar programmes for IIT and Great Lakes. He has worked with companies Like IBM, EDS & Cognizant. 361DM makes you industry ready as the courses focus on three industry relevant aspects – 1) Technical skills like Hadoop and R 2) Better understanding of the business requirements 3) Knowledge of Data Science – statistical inference, mathematical modelling and data visualisation. 361DM experts focus on upskilling thereby providing one-on-one assistance to help you identify your target jobs, spruce up your resume and prep for the analytics interview. 361DM offers program variant giving Placement Assurance for select students. Receive constant guidance from our experienced faculty on job applications. For assistance, check your eligibility with career consultant. Program Suggestion Program Name: Business Analyst Program designed for: Freshers /Experienced Eligibility: Mcom, Msc- Stats, Maths /MBA Eligibility Process: NA Duration: 212 Hours Fees: 825 USD Installment pattern available (Y/N): Yes Program Outcome: To provide complete knowledge about Big Data by covering advanced concepts like R , GGPLOT, Line, Bar and Scatter with GGPLOT2 and Text mining. [-]

Course: Big Data Analytics - Data Engineer

361 Degree Minds
Online Full time 232 hours July 2017 India India Online

You would have probably heard that Big Data and Analytics is one area of technology consisting of skills gaps. What corporate really mean by “skill gap” is that there aren’t enough engineers with the right mix of technical ability, skill of understanding business requirement and knowledge of data science, the three main ingredients of Big Data Analytics. [+]

Top Online Courses in IT. Course: Big Data Analytics - Data Engineer Do you want to be the one of the best sought after engineer in the BIG Data Analytics Industry? You would have probably heard that Big Data and Analytics is one area of technology consisting of skills gaps. What corporate really mean by “skill gap” is that there aren’t enough engineers with the right mix of technical ability, skill of understanding business requirement and knowledge of data science, the three main ingredients of Big Data Analytics. 361DM has the comprehensive solution for Engineers and make them data-savvy professionals. We train the students depending on the current skills required by the corporate world. Be a part of 361DM. Grab the opportunity and get the right platform to enter the Big Data Analytics Industry. Do you want to find "Big Picture" on Big Data? Big Data means Big Opportunities. Big Data analytics sector in India is expected to reach $16 billion industry by 2025. The opportunities for Engineering students in Big Data are vast. Big Data is growing at an unprecedented pace and is sure to offer the students plenty of opportunities to grow towards a secured future. Students who choose to study Big Data Analytics benefit by practicing and developing their critical thinking, management, and communication skills that will be vital to their success in corporate environment. Without the needed Big Data skills, plenty of jobs go unfilled. Getting certified in Big Data technology like Hadoop, programming with R and SQL, making data sets, etc. Will have a rewarding career and definitely assist the students in getting placed during on campus/ off campus recruitment. Some big companies hiring Big Data professionals in India are Accenture, American Express, Dell, Datamatics, eBay, Evalueserve, Genpact, HP, HSBC, IBM, Wipro, SBI, Infosys, IGate, etc. Why Big Data is relevant for Engineering students? Demand for Computer Systems Analysts with big data expertise increased 89.9% in 2015. The data science and big data discipline is strongly connected with and IT engineering , business and applied mathematics. Big Data Analytics is the fastest evolving concept in the IT world now. Students must gain knowledge on this fast-changing technological direction. With ever-increasing size of data sets, there is requirement for professionals to handle Big Data storage, processing, analysis, visualization, and application issues on both corporate workplaces and research environment. New tools and algorithms are being defined and implemented in the corporate world. Computer students can get familiarised with such tools, algorithms and platforms to use it on real time cases. Want to become a Big Data professional….. Do a self analysis to see if you have what it takes. Depending on your expertise, your contributions can have an impact at different points in the Big Data lifecycle of the company you get into. Creativity and problem solving - If you're equipped with a natural desire to know how things work , then you'll always have a job offer waiting somewhere Statistical and quantitative analysis - This skill is the engine for Big Data. If you have a strong mathematical, statistical and analytical skills as well as business strategy thinking, then you have a very bright chance to shine. General purpose programming languages - Engineers having experience in programming applications using general-purpose languages like Java, C etc could give you the edge over other candidates when making the Big Data transition. Story telling with data - Ability to create visualization that tells a story through the graphical depiction of statistical information will be a big plus to the data analytics process in organisations looking to make info more understandable to business executives. Why 361DM is the best in the industry to bring out the Big Data Analytics professional in you? The instructors of 361 Degree Minds are one of the leading industry experts in Big Data. Gain all the recognised qualification & certifications you need for a genuinely desirable Big Data Analytics career. 361DM provides a platform for learning evolving technologies that industry thought leaders consider being disruptive. Big Data Analytics course has been designed by Mr. Suresh Krishnaswamy, a veteran in the Analytics industry. 361DM has clients like Cognizant, Nokia Siemens, Sandisk, Manhattan Associates. 361 DM has 40,000 learners from 18 countries for various programs By learning Big Data with 361DM, sharpen your core skills in Big Data which are. You will get the opportunity to work with real-world data-sets and projects that prepare them to solve complex problems. 361DM offers program variant giving Placement Assurance for select students. For assistance, check your eligibility with career consultant. Program Suggestion Program Name: Data Engineer Program designed for: For Engineering Students - Fresher Eligibility:BE - CS , IT ,ECE / Btech -IT, MCA/M.Sc CS & BSc - CS Eligibility Process: NA Duration: 232 Hours Fees: 720 USD Installment pattern available (Y/N):Yes Program Outcome: This is a expert level program designed to familiarize the learners with concepts like Mathematics Modelling, Making Data Sets, Hadoop Fundamentals, Hadoop Administration, Hadoop Clusters, Programming with R and SQL. [-]

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 IT. 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. [-]

ITIL® Intermediate Level - Planning, Protection & Optimisation (PPO) Training & Exam Package

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

Specialise on the practical application of PPO practices and get certified with this complete ITIL® Planning, Protection and Optimization training and exam package. [+]

What are the objectives of this course? The ITIL® PPO course takes students through the practical application of PPO practices in order to enable capacity, availability, IT service continuity, information security and demand management while demonstrating how to implement them into a modern IT service. How to plan and provide sufficient capacity to support the changing needs of a business. How to specify and implement high availability systems to maintain service quality at all times. Using IT service continuity principles to maintain quality of service as systems and frameworks transition. How to build frameworks and systems that help support demand management. Building a PPO team and assigning roles and responsibilities. Using technology to support PPO goals and services. Who is it intended for? The course suits students who are IT professionals, have their ITIL® Foundation Qualification and work in areas such as IT operations, network support, network control and operation, security manager and security administrator. Requirements In order to take the Planning, Protection and Optimization 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 Planning, Protection and Optimization exam has been passed you will be able to function in roles such as security manager, network support or change 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. [-]

CHFI (Computer Hacking Forensic Investigator) - Training Programme

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

Master the processes and tools required to investigate a serious security breach using industry-standard principles with this Computer Hacking Forensic Investigator (CHFI) course. [+]

Top Online Courses in IT. What are the objectives of this course? This course covers everything needed to investigate, document and prosecute a malicious security breach. How to carry out an investigation according to industry best practice principles and legal guidelines. Searching and seizing resources required for the investigation. Handling Digital Evidence First Responder Procedures How to fit a forensic lab for investigations. Hard Disks and File Systems Windows Forensics Data Acquisition and Duplication Recovering Deleted Files and Partitions Using Access Data FTK and Special Steps EnCase Stenography Passwords Log Correlation Network Forensics Wireless Attacks Web Attacks Email Crimes Mobile Resource Investigation Investigation Reports Expert Witness Who is it intended for? This course is ideal for anyone who has looking to build on their foundational ethical hacking skills. Requirements There are no official pre-requisites for this course but we recommend students have a basic knowledge of computer security and ethical hacking. What marks this course apart? Once students have completed this course they will be ready to sit their CHFI EC0 312-49 exam. Candidates will be able to function in roles such as forensic analyst, security analyst and information security analyst. These jobs usually average a salary of £27,000 a year. Source: PayScale 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. [-]