Developed to provide the foundations of a career in Data Science, the six-week course equips beginners with technical skills and the theoretical knowledge needed to apply the powerful insights of data science to their work.

Overview

The course, exclusively designed by the world-leading Data Science team at the University of Southampton, provides a hands-on approach to learning data skills. Through a number of interactive, online exercises, you will be able to try out many of the concepts and techniques studied in the taught material.

We use Python to implement technical aspects of the course and we strongly advise all applicants have some experience with Python or similar languages.... [-]

About this course

Developed to provide you with the theoretical knowledge, alongside the practical and technical skills, needed to take part in the data revolution, the six-week course helps you to contribute to and benefit from the expanding data-driven economy. It takes a hands-on approach to the learning of data skills through a number of interactive, online exercises, designed to allow you to experience real examples of the techniques and concepts covered in the taught material.

The course is delivered online, and each week is taught using a mixture of self-study and tutor-led material, activities and practical exercises.

If you are interested in the technical approaches to this topic, we currently have a parallel course in Fundamentals of Data Science (Technical)... [-]

Modern Methods in Data Analysis

During this online course, you will learn to use statistical methods to study the association between (multiple) determinants and the occurrence of an outcome event. The course will begin with an introduction to likelihood theory, using simple examples and a minimum of mathematics. You will then move to learning about the most important regression models used in medical research. These include logistic regression, Poisson regression, analysis of `event history´ data, and the Cox proportional hazards regression model. In addition, you will become familiar with model validation and regression diagnostics, as well as with the basic principles of resampling methods and longitudinal data analysis. The course is aimed at professionals who are interested in to learn more about statistics for medical research. However, a medical education is not a requirement to successfully participate in this course.... [-]

Classical Methods in Data Analysis

This online medical course, offered by the MSc Epidemiology program of the UMC Utrecht and Utrecht University, provides an understanding of the basic applications of biostatistics in the analysis of medical research data.

Topics are types of data, location and variability measures, samples and populations, distributions, confidence intervals, hypothesis testing, comparing two or more means or proportions (parametric and non-parametric methods), and relationships between two variables (correlation, simple linear regression). The course also includes an extensive discussion of the multiple linear regression models. This is an ideal course for anyone who wishes to further his medical education by getting a better understanding of data analysis.... [-]

A perfect blend of Technology, Data Science and business cases and insights, this program stands out as among the best in the world. Course Highlights

Real-time Internship

An internship allows you to apply classroom knowledge in real life situations. We help you find relevant work experience opportunities in organizations involved in Big Data Analytics.

Placement Support

Our Placement Division helps our students meet companies that practice Big Data Analytics. Our Placement Division has positioned students in some of the top companies like Siemens, American Megatrends, Dell, and HCL.

Training Methodology

This course involves several hours of Live Faculty session and recorded live session. It also has multiple guest lectures every month. Along with live classes, the course has industry catalyzers, opinion polls, observers, and self-assessments.... [-]

What are the objectives of this course?

In this course, candidates will fully understand the concepts behind Microsoft SQL Server 2012 and how to build and query complex database solutions in a real-world environment. Students will also get 12 months access to our dedicated Live Labs where they will be able to recreate course scenarios and design new database solutions without building a costly lab of their own.

Microsoft 70-641: Querying SQL Server 2012 Microsoft 70-462: Administering SQL Server 2012 Databases Microsoft 70-643: Implementing a Data Warehouse with SQL Server 2012

After completing the three MCSA SQL Server 2012 modules, students will then shift focus to the elements that make the MCSE SQL 2012 Data Platform with two additional modules.... [-]

What are the objectives of this course?

This course will fully prepare students for the three respective module exams that make the MCSA Windows 7 qualification. It will help you demonstrate the knowledge and skills in working with Windows 7 and validate your ability to support end users while maintaining the system and mobile devices. Live Labs are included in this package and are seen as an essential learning resource for students as it allows them to test their knowledge and skills in practice exercises and environments without the need to invest in a costly test lab of their own. Microsoft 70-680: Configuring Windows 7

Installing, Upgrading and Migrating to Windows 7 Deploying Windows 7 Configuring Hardware and Applications Configuring Network Connectivity Configuring Access to Resources Configuring Mobile Computing Monitoring and Maintaining Windows 7 Systems ... [-]

What are the objectives of this course?

The course will run students through the functions of Perl which is one of the original program languages and fully prepare them for their 1D0-437 exam. The examination has a time limit of 75 minutes, in which candidates have 50 questions to answer. In order to pass, you must achieve a minimum pass mark of 75%.

Introduction to Perl The uses of the Perl interpreter and understand how to operate the interpreter. Understand the concepts of statements, loops, and Boolean expressions. Learn how to manipulate strings using regular expressions and store program data using arrays. Manipulate data with keys and use hashes to organize the data. Use subroutines to organize code to make it more logical and easier to debug. Implement object-orientated programming techniques using Perl. Debugging Perl. Basics of database programming Who is it intended for? ... [-]

What are the objectives of this course?

This course will help programmers of all levels get to grips with every function that the Perl programming language has to offer.

Perl language essentials including syntax, regular expressions, and data types. Server scripting, focusing on Perl language. Perl code development including access and manipulating input and output files. Implement websites including database connectivity and debugging techniques. Improve and maintain hypertext-based websites. Understand how to debug Perl Object-Oriented Perl Database connectivity and Perl Who is it intended for?

This course is suitable for anyone, from beginners looking to learn about Perl programming language to IT programmers who are looking to enhance their skill set by learning new web scripting techniques.... [-]

Learn to gather, analyze, and tell stories through data with SQL, Excel, and visualization.

Model Behavior

Whether you’re using data to make business, technology, or design decisions – the process is the same.

Problem Formulation & Experiment Design

Properly define a problem and design tests that get valid results.

Extraction & Scrubbing

Use SQL to extract data from databases, then clean and prepare it for analysis.

Data Analysis

Use basic statistics and Excel to manipulate data in order to find patterns and answer questions.

Narrative & Visualization

Communicate findings effectively using data visualization, dashboards, and presentations.... [-]

Intensive 6-Month Program Collaborative Assignments with Mentors Master Statistics, Machine Learning, Deep Learning, and AI Learn Tools like Python, TensorFlow, Spark, R, and Tableau

DURATION

24 Weeks

EFFORT

10-15 Hrs/Week

CAREERS

Business Analyst, Data Analyst, Data Architect, Data Administrator, Data Manager, Data Scientist

The course teaches statistics for business analysis, machine learning algorithms, deep learning with TensorFlow, and programming with Python. It will help you explore, analyze, and interpret different kinds of data.

Why You Should Take This Course Acadgild Experience What You Will Learn in This Course Programming in Python and R Python & R basics Conditional and loops String and list objects Functions & OOPs concepts Exception handling Database programming*Sessions on R are not live, but self-paced Data Wrangling Reading CSV, JSON, XML and HTML files using Python NumPy & pandas Scipy libraries Loading, cleaning, transforming, merging, and reshaping data Statistics and Probability Descriptive statistics Inferential statistics Hypothesis testing Statistical concepts in Python Machine Learning Models with Python Building models using algorithms Linear and logistics regression Decision trees Support vector machines (SVMs) Random forests XGBoost K nearest neighbor & hierarchical clustering Principal component analysis Text analytics and time series forecasting Deep Learning using TensorFlow Introduction to deep learning Understanding neural network through TensorFlow Convolution & recurrent neural networks Data Visualization using Matplotlib and Tableau Interactive visualizations with Matplotlib, Data visualizations using Tableau Tableau dashboard and storyboard Tableau and R integrationSessions on Tableau are not live, but self-paced Handling Big Data with Spark Introduction to Big Data & Spark... [-]

Policy is the art of achieving the desired outcome in the presence of constraints and differing priorities.

Policy is largely a coordination problem. Here data and models can help. The Ebola outbreak in West Africa did not spread worldwide because science-based policies were implemented, replacing ineffective policies such as restricting movement by closing borders.

Model policy problems with Global Systems Science

The science of epidemics is one of the successes of Global Systems Science (GSS) – an interdisciplinary approach to modelling the complex, multi-faceted and intertwined problems of the modern world. Another example is the use of network science in financial regulation dealing with many interconnected financial actors.... [-]

Learn how to get the most from healthcare data using process mining

Within healthcare, there are thousands of complex and variable processes that generate data including treatment of patients, lab results, and internal logistic processes. Analysing this data is vital for improving these processes and ending bottlenecks.

On this course, you will explore how process mining can help turn this data into valuable insights by looking at different areas of process mining and seeing how it has been applied. You will even get the chance to apply process mining to real life healthcare data.

What topics will you cover?

Process mining provides a critical, process-centric perspective on data, which is not available with classical data mining or machine learning techniques. Applying process mining in the healthcare environment is extra beneficial since processes are complex, and costs are high.... [-]

Open Data is data that anyone can access, use or share and when used well it can be extremely powerful. It enables businesses, citizens, developers, and researchers to harness resources that can make crucial improvements to their communities and the economy. It can also help with the development of new products and services, improve business efficiency and create economic value.

This course provides new insight into the history of Open Data, its pros and cons, business cases and business models related to publishing and using Open Data.

How could you benefit? Join to find out.

What topics will you cover? What is Open Data? Why is Open Data useful in business? How to assess and manage risk when using Open Data How Open Data can improve business How to create an Open Data business model How to use external Open Data How to publish Open Data What will you achieve? ... [-]

Extend your repertoire of data mining scenarios and techniques

This course will bring you to the wizard level of skill in data mining, following on from Data Mining with Weka and More Data Mining with Weka, by showing how to use popular packages that extend Weka’s functionality. You’ll learn about forecasting time series and mining data streams. You’ll connect up the popular R statistical package and learn how to use its extensive visualization and preprocessing functions from Weka. You’ll script Weka in Python – all from within the friendly Weka interface. And you’ll learn how to distribute data mining jobs over several computers using Apache SPARK.

What topics will you cover? Time series analysis Data stream mining Incremental classifiers Evolving data streams Support vector machines Accessing data mining in R Distributed data mining Map-reduce framework Scripting data mining in Python and Groovy Applications * Soil analysis * Sentiment analysis * Bioinformatics * MRI neuroimaging * Image classification What will you achieve? ... [-]