COURSE ID – DBAL-104     DURATION – 64 Hours

Program Objective
As the popularity of R and Python is increasing steadily, learn how these languages can be used to carry out advance analytics. This course starts from the very basics (Introduction to R and Python programming, data importing, data manipulation, basic statistical concepts, etc.) to advanced topics (Predictive Analytics, Forecasting, etc.). Teaching methodology will include a high focus on core concepts along with implementation on varied industry use-cases. Participants will be awarded a Python-R Data Scientist Certification on completion of this course.
After the completion of Data Science using R and Python course, you will be able to:

  • Use R and Python for data importing, basic and advanced data manipulation, data analysis and visualization
  • Use R and Python for handling large data sets with optimized manner
  • Work on Advanced and predictive analytics techniques using R and Python/li>
  • Work on end to end data science projects using R and Python
Who Should do this course?
This Data Science using R-Python certification course is for all those aspirants who want to switch into the field of data science/ business analytics and are keen to enhance their technical skills with exposure to cutting-edge practices
The Students/professionals/Candidates from various quantitative backgrounds, like Engineering, Finance, Maths, Statistics, Business Management who want to head start their career in analytics.
There are no prerequisites for this course. Knowledge of any programming and data analytics exposure would be an advantage. For beginners, its highly recommend to complete the “Data Analytics using Excel – Tableau” course prior to this course.
Modules & Topics


  • Introduction to Data Science


  • R-Introduction – Data Importing/Exporting
  • R – Data Manipulation
  • R – Data Analysis – Visualization


  • Python: Introduction – Essentials
  • Python: Accessing/Importing and Exporting Data
  • Python: Data Manipulation – cleansing
  • Python – Data Analysis – Visualization
  • Python: Polyglot Programming

R & Python: Basic Statistics

  • Basic Statistics – Hypothesis Testing – Statistical Methods

R & Python: Data Preparation

  • Predictive Modeling – Introduction- Steps
  • Data Preparation for Predictive Modeling – Factor Analysis

R & Python: Predictive Modeling

  • Predictive Modeling – Segmentation
  • Predictive Modeling – Decision Trees
  • Predictive Modeling – Linear Regression
  • Predictive Modeling – Logistic Regression
  • Predictive Modeling – Time Series Forecasting

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