Data Science with SAP

An Ultimate Hands On Masterclass for Applying Machine Learning, Data Science techniques on SAP Data to derive insights

Language: English

Instructors: Manifold AI Learning®

$199 92.47% OFF

$14.99 including GST

PS : First Time Students get 10% Additional Off


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One-Time Payment & Lifetime Access

$199 92.47% OFF

$14.99 including GST

PS : First Time Students get 10% Additional Off


    Get Exclusive Benefits

  • Course Completion Certificate
  • Instant Access
  • Expert Instruction
  • Curated by Experts

This course includes:

  • 21 hours on-demand video
  • 22 Articles for download
  • 60+ downloadable resources
  • Access from Any Device
  • Assignments
  • Full Lifetime Access

Check out our course Trailer!!

What do our students say

Excellent course, extremely simplified and broken down to small steps to follow easily. That's great content to follow— Dave Smith

this is a real hands-on course. I liked the assignment at the end of each new topic. Keeps me on track and learn at the same time —  Wang

I really liked the flexibility of this course. It worked well with busy scheduling— Jane Doe

Why this course?


This course has been created to bridge the gap between SAP Professionals and Data Scientists. As you progress in this learning journey, You will realize that most of the Activities performed by Data Scientists are very much similar to the way we SAP Professionals implement the Business Requirements on an ERP Software - SAP. The key difference is: Data Scientists know how to ask better questions on the data


To bridge this gap, we have designed this curriculum of Data Science for SAP Professionals which encompasses a wide range of topics.

  • Understanding of the data science field and the type of analysis carried out
  • Statistics
  • Python
  • Applying advanced statistical techniques in Python
  • Data Visualization
  • Machine Learning
  • Using Pretrained Models like Google Cloud Natural Language Processing API to have a Jumpstart for your SAP Application implementation.

Each of these topics builds on the previous ones. Due to this reason, we recommend you acquire these skills in the right order as mentioned in our curriculum so that,  it won't be an overwhelming experience for a learner.

So, in an effort to create the most effective, time-efficient, structured, and business case-driven data science training available online, we have created this course: Data Science with SAP - Machine Learning for Enterprise Data

We believe this is the first training program that solves the challenge of SAP professionals to entering the field of data science by enabling the learners to have all the necessary resources in one place.

The focus of our course is to teach topics that flow smoothly and complement each other and can be easily related to Enterprise Data SAP. The course teaches you everything you need to know to become a data scientist from SAP Consultant at a fraction of the cost of traditional programs (not to mention the amount of time you will save).


***What you get***

  • A $3000 data science training program
  • Active Q&A support
  • All the knowledge to get hired as a data scientist for SAP Applications
  • A community of data science learners
  • A certificate of completion
  • Access to future updates
  • Solve real-life business cases that can be easily extended to your business application


You will become a data scientist from scratch using SAP Data

We are happy to offer an unconditional 30-day money-back in the full guarantee. So, No risk for you. The content of the course is excellent, and this is a no-brainer for us, as we are certain you will love it.

Why wait? Every second is a missed opportunity.

Click the “Buy Now” button and become a part of our data scientist program today.

What you’ll learn

  • Course Provides the Entire Toolbox you need to apply Data Science – Machine Learning Algorithms for your SAP Data
  • Get ahead of crowd by knowing the hottest skill in the current Market
  • Start coding in Python and learn how to use it for Statistical Analysis of SAP Data
  • Be able to create Machine Learning algorithms in Python, using NumPy, statsmodels and scikit-learn – Essential tools for Performing Data Science with SAP Data
  • Carry out cluster and factor analysis on SAP Data
  • Learn to Extract the Required Data from SAP System to perform Statistical Analysis & Apply various Machine Learning Models
  • Learn how to pre-process the extracted data from SAP
  • Apply the Skills to real-life business cases
  • Be Industry Ready to apply everything you have learnt to more and more real-life scenarios in the ocean of SAP
  • Build Recommendation Engine Using SAP Data
  • Create a Project Implementation to Perform the Predictive Analytics on SAP Data & Perform the Advanced Time Series Analysis using ARIMA Model
  • Learn to use Advanced Techniques, and make use of Pre-trained Model from Google Cloud Natural Language Processing API for Text Data

Are there any course requirements or prerequisites?

  • No Prior Experience is required. We start from the very basics
  • You will need to install Anaconda. We will show you how to do that – Step by Step
  • Basic Familiarity with SAP Interface (Optional)

Who this course is for:

  • SAP Functional & Technical Consultants who wants to Jump into the field of Data Science
  • You should take this course if you want to become a Data Scientist , and learn how to get the Business insights by using the data from SAP System
  • This course is for you if you want a great career
  • The course is also ideal for beginners, as it starts from the fundamentals and gradually builds up your skills
  • Data Scientists who are interested in learning how to perform various activities from SAP Data

Course Curriculum

About our Course (2:00) Preview
Getting System Ready
About Python Programming Language - Anaconda Installation (5:00) Preview
Resources for Help in Installation
Start Jupyter Notebook (2:00) Preview
Start iPython Notebook (2:00)
Default Folder Path of ipython notebook files (2:00)
Jupyter Notebook Guide (16 pages)
Python Programming
Section Attachments - Python Programming Basics
Taste of Py (7:00)
Variables in Python Programming Language (4:00)
Variable Creation Assignment
Rules for Creation of Variables in Python (11:00)
Assignment: Rules for Creation of Variables
Data Types in Python - Numerical (8:00)
Activity - 3: Creation of Variables & Display its Data Type
Working in Jupyter Notebook (3:00)
Working in Jupyter Notebook - Hands On Exploration (12:00)
Data Types in Python - Boolean & Sequence (5:00)
Data Types in Python - Boolean & Sequence - Hands On (8:00)
Data Types in Python - Dictionaries & Sets (3:00)
Data Types in Python - Dictionaries & Sets - Hands On (6:00)
Operators in Python (9:00)
Operators in Python - Hands On (7:00)
Adding the Comments in Python (7:00)
Adding the comments in Python - 2 (8:00)
Working with Print Function (4:00)
Exploring Print Function (13:00)
Type Casting in Python Data Type Conversion (3:00)
Type Casting in Python (9:00)
Getting Input from User (8:00)
Control Statements in Python
Section Attachments - Control Statements in Python
Control Statements in Python - If (10:00)
Control Statements in Python - If (15:00)
Logical Operators (3:00)
Logical Operators on Conditional Statements (7:00)
Control Statement - if_else (8:00)
Control Statements - if_elif_else (5:00)
Control Statements - if elif else - Python (7:00)
Control Statements - While loop (6:00)
Control Statements - While loop - Python (15:00)
Control Statements - For loop (4:00)
Control Statements - For loop - Python (11:00)
Control Statements Break , Continue & Pass (5:00)
Control Statements Break , Continue & Pass - Python (10:00)
Data Structures in Python
Section Attachments - Data Structures in Python
Intro to Data Structures (2:00)
Lists in Python (10:00)
Python lists - Jupyter Notebook (11:00)
Python Tuples (3:00)
Python tuples - 2 (6:00)
Python Dictionaries (6:00)
Python Dictionaries - Hands On (9:00)
Sets in Python (6:00)
Sets in Python - Hands On (4:00)
Sets - Operations (11:00)
Strings (4:00)
Strings - Hands On (5:00)
Strings - Other Methods (6:00)
Negative Indexing and Escape Characters (7:00)
Functions & Classes in Python
Section Attachments Functions & Classes in Python
Functions in Python (12:00)
Functions - Contd (8:00)
Calling Functions inside a function (10:00)
Object Oriented Python (9:00)
Working with Classes and Objects in Python (16:00)
Capstone Project using Python Programming
Section Attachment - Capstone Project
Intro Capstone Project (7:00)
Selecting the Random Word for the Game (6:00)
Initializing the Game (7:00)
Logic of word validation (8:00)
Logic for Letter Validation (13:00)
Final Testing (6:00)
Numpy for Data Science
Section Attachment - Numpy for Data Science
Introduction to Numpy Library (7:00)
Basics of numpy array object (4:00)
Import Numpy & Access help (5:00)
Creation of Array Object - np.array() (5:00)
Attributes of Numpy Array (4:00)
Array Indexing and Slicing (10:00)
Array Creation Functions (11:00)
Copy Arrays (5:00)
Mathematical Operation on Numpy Arrays (4:00)
Linear Algebra Functions in Numpy (3:00)
Shape Modification of Arrays (10:00)
np.arange() (4:00)
Relational Operators & Aggregation Functions on Numpy Arrays (7:00)
Boolean Masking (2:00)
Broadcasting on Numpy Arrays (19:00)
Summary of Numpy Library Journey (4:00)
Pandas for Data Science
Section Attachment - Pandas Library for Data+Science
Introduction to Pandas (5:00)
Working with Pandas Series (9:00)
Mathematical Operation on Pandas Series (3:00)
Dataframes in Pandas (13:00)
Working with Data in Pandas DataFrame (9:00)
Combining the DataFrames (10:00)
Other Functions on Pandas DataFrame (11:00)
Advanced Functions in Pandas DataFrame (21:00)
Exploratory Data Analysis
Section Attachment : EDA on Large Dataset
Introduction to EDA (3:00)
Accessing Google Colab (5:00)
Access Google Colab (5 pages)
Loading the Large Dataset for Working (7:00)
Preliminary Analysis on DataFrame (15:00)
Null values in the Dataframe (7:00)
Data Cleaning (10:00)
Data Visualization - Matplotlib
Section Attachment - Matplotlib for Data Science
Introduction to Data Visualization (6:00)
Matplotlib Basics (10:00)
Types of Plot - Line plot (3:00)
Line Plots Hands On (10:00)
Adjusting the Plots (9:00)
Plot Adjustment Hands On (8:00)
Scatter Plot (4:00)
Scatter Plot hands on (10:00)
Historgram Plot (6:00)
Data Visualization - Seaborn
Section Attachment - Seaborn for Data Science
Introduction to Seaborn (3:00)
Exploring the data (10:00)
Univariate & Bivariate Plots - Continuous Data (11:00)
Plot - Categorical Data (9:00)
Advanced Plots in Seaborn (7:00)
Which Plot to use ? (5:00)
Intro to Data Science - Machine Learning with SAP Data
Intro to ML DS with SAP Data (20:00)
Clustering on SAP Data - Mastering KNN Algorithm
Section Attachment : Mastering KMeans Algorithm
Understanding Clustering (10:00)
Mathematical Working of KMeans (13:00)
Apply KMeans on an Example Dataset (16:00)
Explore KMeans() class (15:00)
Measure Cluster Quality (6:00)
Measure Cluster Quality - Hands On (14:00)
List Comprehension (8:00)
Scaling the Data with Standard Scaler (14:00)
Clustering on ML Example Data (10:00)
Clustering & Segmentation -Implementation on SAP Data
Section Attachment : Clustering with SAP Data
Project Overview (7:00)
Data Extration Steps : SAP (8:00)
Data Loading & Transformation (12:00)
Data Transformation (12:00)
Apply KMeans on SAP Data (8:00)
Summary of KMeans (2:00)
Build Recommendation Engine Using SAP Data
Section Attachments : ARULES MINING
Section Overview & Introduction to Recommendation Systems (11:00)
Hands On Overview (2:00)
Data Transformation & Data Manipulation (16:00)
Generate Association Rules (8:00)
Data Extraction from SAP (2:00)
Association Rule Program (4 pages)
Custom Program in SAP ABAP for Data Extraction (4:00)
Data Extraction using SQVI (5:00)
Data Preparation of External File (17:00)
Data Pre-Processing on Extracted SAP Data (7:00)
Generate Association Rules on SAP Data (7:00)
Summary - Association Rule Mining (2:00)
Predictive Analytics on SAP Data - Time Series Forecasting
Section Attachment : Predictive Analytics on SAP Data - Time Series Forecasting
Learning Objectives & Section Overview (2:00)
Why do we require Forecasting ? (2:00)
Understand Forecasting (7:00)
Project Overview (2:00)
Data Extraction from SAP System (5:00)
Data Loading & Manipulation (16:00)
Understand the Time Series Data (7:00)
Knowledge Check (7:00)
Quick Recap (2:00)
Differencing Hands On (5:00)
Data Loading & Preliminary Analysis - Hands On (6:00)
Hypothesis Testing (6:00)
Hypothesis Testing Hands On - ADF Test (8:00)
AutoCorrelation in Time Series Plot (10:00)
AutoCorrelation Hands On (4:00)
Features of ACF plot (5:00)
Relation Between ACF Plot & Time Series Plot (10:00)
Introduction to ARIMA (6:00)
Understanding p & q in ARIMA (2:00)
Overview of Hands On Implementation of ARIMA
ARIMA Hands On (19:00)
Project Completion - ARIMA Model on SAP Data (4:00)
Time Series Analysis Flow Chart - Summary (3:00)
Natural Language Processing with Google Cloud API - Text Data
Section Attachment : Natural Language Processing with Google Cloud API -Text+Data
Learning Objective & Section Overview - NLP
Overview of NLP - Natural Language Processing (3:00)
Text Pre-processing techniques (7:00)
Setting up Google Cloud Account (6:00)
Load the Dataset (4:00)
Connecting with Google Cloud Natural Language API (11:00)
Summary - NLP with Text Data - Classification (3:00)

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