The proliferation of new technologies such as mobile, cloud computing, and artificial intelligence have transformed customer behavior and disrupted the marketplace. As a result, our marketing practices must also evolve. Marketing in a digital world is much more than marketing through digital channels. It's about harnessing automation to make marketing practices more productive and agile. It's about mining new sources of customer data to create personalized. communications. And it's about leveraging analytics and AI (artificial intelligence) to optimize marketing activities.

Kellogg Executive Education is a thought leader in understanding how new technologies continue to transform marketing practice. Professor Mohanbir Sawhney—a globally-recognized scholar, educator, and author at the intersection of marketing, innovation, and technology—will guide you through a strategic deep dive into modern marketing practices.... [-]

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... [-]

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.... [-]

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.... [-]

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.... [-]

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 ... [-]

Course overview

This online course is designed for anyone looking to review their Google Analytics activity and take it to an advanced level. Full guidance is offered on key foundational elements, before moving on to advanced tools and techniques to deliver the highest levels of actionable insight.

Key benefits

Take these learning outputs away with you:

Draw actionable insight

Learn best practice use of Google Analytics reports and data

Closely measure ROI

Measure and compare performance across each of your marketing channels

Mine your analytics data

Move beyond standard reporting activity

How it works Live, trainer-led class ... [-]

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? ... [-]

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? ... [-]

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.... [-]

What do social statistics and economic data really reveal?

Increasingly, we’re bombarded with all sorts of data about how society is changing. From opinion poll trends and migration data to economic results and government debt levels.

On this course from the Sheffield Methods Institute at University of Sheffield, we’ll look at ways of cutting through the confusion to decide what numbers reveal, when and why they (sometimes deliberately) mislead and determine what is ‘fake news.’

What topics will you cover? Recognising the ‘size’ of numbers that are reported in the media. How change and risk are reported. How social statistics are created, paying particular attention to survey data. What we can learn from census categories. The different ways that surveys can be conducted and the impact that different formats can have on the results. How to draw a representative sample from a population. Sources of measurement error in surveys. Measuring sensitive or difficult subjects. Checking whether data is trustworthy by reviewing the methodology. How to calculate the Margin of Sampling Error (MoSE). The difference between correlation and causation. Where to find existing sources of data. How to develop a quantitative research project. What will you achieve? ... [-]

This online course will introduce you to various high-performance computing (HPC) facilities for big data analysis. This includes R – a programming language renowned for its simplicity, elegance and community support – and Hadoop – an open source, Java-based programming framework for large datasets. You will find out how to use them, avoiding common pitfalls and saving you time and money.

What topics will you cover? First steps in R and RStudio Working with Apache Hadoop 1 – Fundamentals Working with Apache Hadoop 2 – RHadoop Statistical learning using RHadoop What will you achieve?

By the end of the course, you will:

Understand how the performance of modern supercomputing is achieved Understand the basic functionality of the Bash terminal window Understand the basic functionality of Apache Hadoop for scalable, distributed computing Understand the basic functionality of RHadoop Understand the basic problems of supervised and unsupervised learning Perform basic clustering, regression, and classification with RHadoop. [-]

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.... [-]