Set yourself on the path to becoming a successful SAP EWM consultant

Chapter 1 – Python Basics
Chapter 2 – Python Data Structures
Chapter 3 – Python Programming Fundamentals
Chapter 4 – Working with Data in Python
Chapter 5 – Working with NumPy Arrays

Chapter 1 – Data Science Overview
Chapter 2 – Data Analytics Overview
Chapter 3 – Statistical Analysis and Business Applications
Chapter 4 – Python Environment Setup and Essentials
Chapter 5 – Mathematical Computing with Python (NumPy)
Chapter 6 – Scientific computing with Python (Scipy)
Chapter 7 – Data Manipulation with Pandas
Chapter 8 – Machine Learning with Scikit–Learn
Chapter 9 – Natural Language Processing with Scikit Learn
Chapter 10 – Data Visualization in Python using matplotlib
Chapter 11 – Web Scraping with BeautifulSoup
Chapter 12 – Python integration with Hadoop MapReduce and Spark

Chapter 1 – Introduction to Artificial Intelligence and Machine Learning
Chapter 2 – Data Wrangling and Manipulation
Chapter 3 – Supervised Learning
Chapter 4 – Feature Engineering
Chapter 5 – Supervised Learning-Classification
Chapter 6 – Unsupervised learning
Chapter 7 – Time Series Modelling
Chapter 8 – Ensemble Learning
Chapter 9 – Recommender Systems
Chapter 10 – Text Mining

Chapter 1 – Getting Started with Tableau
Chapter 2 – Core Tableau in Topics
Chapter 3 – Creating Charts in Tableau
Chapter 4 – Working with Metadata
Chapter 5 – Filters in Tableau
Chapter 6 – Applying Analytics to the worksheet
Chapter 7 – Dashboard in Tableau
Chapter 8 – Modifications to Data Connections
Chapter 9 – Introduction to Level of Details in Tableau (LODS)

Chapter 1 – Fundamental SQL Statements
Chapter 2 – Restore and Back-up
Chapter 3 – Selection Commands: Filtering
Chapter 4 – Selection Commands: Ordering
Chapter 5 – Alias
Chapter 6 – Aggregate Commands
Chapter 7 – Group By Commands
Chapter 8 – Conditional Statement
Chapter 9 – Joins
Chapter 10 – Subqueries
Chapter 11 – Views and Index
Chapter 12 – String Functions
Chapter 13 – Mathematical Functions
Chapter 14 – Date – Time Functions
Chapter 15 – Pattern (String) Matching
Chapter 16 – User Access Control Functions

Chapter 1 – Introduction to Business Analytics
Chapter 2 – Introduction to R Programming
Chapter 3 – Data Structures
Chapter 4 – Data Visualization
Chapter 5 – Statistics for Data Science I
Chapter 6 – Statistics for Data Science II
Chapter 7 – Regression Analysis
Chapter 8 – Classification
Chapter 9 – Clustering
Chapter 10 – Association