Develop the Skills of a Data Scientist

Data analytics (DA) is the process of examining data sets in order to find trends and draw conclusions about the information they contain. Increasingly data analytics is used with the aid of specialized systems and software.

Goal:                  Forming and Leading Data Teams 

Duration:       4 weeks / 10h per week

Outcome:       Set up of a data team and analytics platform

Coaching:        Group Coaching

Approach:      E-learning Framework with 4 Steps

Price:                    €1,987.00


The pandemic pushed data further into the spotlight — and it’s going to stay there.

The demand for data science skills and data-driven decision making has been rapidly accelerating for years. Now, organizations across industries are putting professionals to the test to understand and respond to the drastic shift in business operations and consumer behavior caused by the COVID-19 pandemic. In a world that’s constantly changing, it’s normal to feel like you don’t have control over what happens next. One thing you can control? Your education. With modular, flexible learning opportunities on this Platform, it’s easy to gain the tangible skills and knowledge you need on your own time and at your own pace.

Analytics and data science have become “essential navigational tools” as businesses respond to the uncharted waters of a pandemic-disrupted economy and prepare for the future. 


As an increasing range of professionals are leveraging data skills to ask questions and explore problems, the types of job functions and industries that use data will only continue to grow.


Opportunities for Impact

There’s a renewed, critical need to untangle, rework, and leverage data to understand new business challenges and find paths forward

Over the past decade, the availability of data and demand for analytics and data science skills has skyrocketed. 

In the sudden, unpredictable market sparked by the pandemic, the data and models companies relied on to inform strategy and decision making have been turned upside down. 

From the race to invest in real-time visualization and reporting capabilities to weather today’s storm to continued focus on building resilient, data-driven organizations, the spotlight on the power and potential of data science and analysis skills has never been brighter.


Data Analytics of the Sales Process

organizations across industries are putting professionals to the test to understand and respond to the drastic shift in business operations and consumer behavior caused by the COVID-19 pandemic.

Data Analytics of the Marketing Mix

Using the Power of Data for better Decisions

Data analysis is a process of inspecting, cleansing, transforming, and modeling data with the goal of discovering useful information, informing conclusions, and supporting decision-making.

Course Outline

Data science and analysis is becoming a 21st century job skill for every discipline.

  • 1

    Business Impact of Data Analytics

  • 2

    Welcome to the course!

    • How to use this course

    • Before we begin...

  • 3

    1) Analytics & Business Transformation

    • Introduction

    • Analytics in Fashion

    • Analytics in Sport

    • Analytics in Hospitality

    • Opinion vs. Big Data

    • Defining Analytics Areas

    • Types of Analytics

    • Use of Analytics

    • Test your learning

  • 4

    2) The Process of Analytics

    • Introduction Process of Analytics

    • Introduction of Analytics Process

    • Process of Analytics

    • Test your learning (1)

    • Tools in the Analytics Process

    • Test your learning (2)

    • Presentation Tools

    • Test your learning (3)

    • Roles in an Analytics Team

    • Test your learning (4)

    • Analytics Key Questions

    • Prospective Questions

    • Test your learning (5)

    • Role of the Data Translator

    • Test your learning (6)

    • Framing a Data Problem

    • Test your learning (7)

  • 5

    3) The Opportunities and Challenges of Data /

    • Introduction

    • Sources of Data

    • External Data Sources

    • Data Provenance

    • Data Logistics

    • Data Storage

    • Data Security

  • 6

    4) Data Mechanics

    • Introduction

    • Data Schemas

    • Data Transformation

    • Advanced Data Transformation

    • Data Cleaning

  • 7

    5) Descriptive Analytics

    • Introduction

    • Installing Power BI Desktop

    • The Contoso Data Set Part 1

    • The Contoso Data Set Part 2

    • Analyzing Data Using Power BI Part 1

    • Analyzing Data Using Power BI Part 2

    • Analyzing Data Using Power BI Part 2

    • Analyzing Data Using Power BI Part 2

    • Analyzing Data Using Power BI Part 3

    • Analyzing Data Using Power BI Part 4

    • Analyzing Data Using Power BI Part 5

    • Defining Calculated Measures Part 1

    • Defining Calculated Measures Part 2

    • Goals of Visualization

    • Seasonality and Trend Analysis

    • Introducing the Yelp Dataset

    • Clustering Using the Yelp Dataset

    • Case Study: The Groupon Effect

    • Case Study: Visualization of The Groupon Effect

  • 8

    6) Predictive Analytics

    • Predictive Analytics Workflow

    • What is Machine Learning?

    • Classification Basics

    • Classification Metrics

    • Classification Metrics

    • Classification in Azure ML

    • Regression Basics

    • Regression in Azure ML

    • Recommender System Basics

    • Recommender Systems in Azure ML

  • 9

    7) Applying Business Analytics

    • Applying Business Analytics

    • Selection Bias

    • Selection Bias: A Real World Example

    • Data Leakage

    • Correlation vs. Causality

    • Multi-Level Models

    • Training/Production Setting Mismatch

    • Presentation of Preliminary Findings by the Data Analyst

    • Feedback from the Data Translator

    • Iterating on the Initial Model

    • Iterating on the Initial Model

    • Final Presentation by the Data Translator

  • 10

    Next steps

    • More resources for you (1)

    • More Resources for you (2)

    • Before you go...

Watch Intro Video

Data Science and AI

The Power of Augmenting Thinking

Dr. Paul Gromball: Program Lead

I help you to achieve your business growth goal without hiring consultants by enabling you and your team with tailored self-service knowledge and skills. Mail: Paul.Gromball@tmg-muenchen.de

Management (CEO) , Consulting (McKinsey) and Learning Experience (MIT, Harvard) of more than 30 years in developing and implementing strategic, operational and organizational performance improvements at global enterprises and medium-sized businesses. Working expertise in a variety of management areas including, strategy, sales-and marketing, cost-reduction, supply chain management, manufacturing (MES), sourcing, IT management,reorganization and M&A/ post merger integration. Focus oncompanies of the Process-Industry (pharmaceuticals, chemistry, steel),Assembly-Industry (automotive, automotive-supplier, engineering,electronics) Consumer Goods (food, clothing, household appliances) and Services (logistics, airlines)