Expert Programmes

Data Science with Python

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(All course fees are in USD)


Course Description

Through this Python for Data Science training, you will gain knowledge in data analysis, machine learning, data visualization, web scraping, & natural language processing.  You will also get equipped to master the essential tools of Data Science with Python


Offered in Partnership with


Course Delivery
  • Online pre-recorded self-paced learning (24 hours)
  • Live virtual classroom training (44 hours).

Total online blended learning: 68 hours


  • Data Science is an evolving field and Python has become a required skill for significant portion of jobs in Data Science.
  • 68 hours of blended learning (24 hours online self-paced learning + 44 hours of instructor-led online training by industry experts)
  • 4 industry-based projects
  • Interactive learning with Jupyter notebooks labs
  • 1 year access


Award upon Successful Completion
Data Science with Python Certificate of Achievement


Awarding Organisation



Learning Outcomes
  • Gain an in-depth understanding of data science processes, data wrangling, data exploration, data visualization, hypothesis building, and testing; and the basics of statistics
  • Understand the essential concepts of Python programming such as datatypes, tuples, lists, dicts, basic operators, and functions
  • Perform high-level mathematical computations using the NumPy and SciPy packages and their large library of mathematical functions
  • Perform data analysis and manipulation using data structures and tools provided in the Pandas package
  • Gain an in-depth understanding of supervised learning and unsupervised learning models such as linear regression, logistic regression, clustering, dimensionality reduction, K-NN, and pipeline
  • Use the Scikit-Learn package for natural language processing and matplotlib library of Python for data visualization




Fulfilling ALL of below:

  • A score of at least 75% in course-end assessment, AND below:
  • Complete 85% of the course
  • Submit at least one completed project, with satisfactory evaluation by instructor.


Course End Projects


Project 1: Products rating prediction for Amazon

Amazon, one of the leading US-based e-commerce companies, recommends products within the same category to customers based on their activity and reviews of similar products.

Amazon would like to improve this recommendation engine by predicting ratings for the nonrated products and add to recommendations accordingly.

Domain: E-commerce


Project 2: Demand Forecasting for Walmart

Predict accurate sales for 45 stores of Walmart, a US-based leading retail stores, considering impact of promotional markdown events. Check if macroeconomic factors, such as CPI and unemployment rate, have an impact on sales.
Domain: Retail


Project 3: Improving Customer Experience for Comcast

Comcast, one of the largest US-based global telecommunication companies wants to improve customer experience by identifying and acting on problem areas that lower customer satisfaction. The company is also looking for  recommendations to achieve satisfactory customer experience.

Domain: Telecom


Project 4: Attrition Analysis for IBM

IBM, one of the leading US-based IT companies, would like to identify factors that influence attrition of employees. Based on the parameters identified, the company would also like to build a logistics regression model that can help predict if an employee will churn or not.

Domain: Workforce Analytics


Who Should Enrol
  • Analytics professionals willing to work with Python
  • Software and IT professionals interested in analytics
  • Anyone with a genuine interest in data science




This Python for Data Science training is beneficial for analytics professionals willing to work with Python, Software, and IT professionals interested in the field of analytics, and anyone with a genuine interest in Data Science.

To best understand the Data Science with Python course, it is recommended that you begin with these courses:

  • Python Basics
  • Math Refresher
  • Data Science in Real Life
  • Statistics Essentials for Data Science
Course Overview
Lesson 01 – Course Introduction
Lesson 02 – Introduction to Data Science
Lesson 03 – Python Libraries for Data Science
Lesson 04 – Statistics
Lesson 05 – Data Wrangling
Lesson 06 – Feature Engineering
Lesson 07 – Exploratory Data Analysis
Lesson 08 – Feature Selection


Accessible Period of Course

1 year from date of enrolment


Customer Reviews


Arvind Kumar

Technology Lead

It was a great learning experience. My trainer, Vaishali delivered each session well. All topics were explained with in-depth theory, real-time examples, and execution of the same in Python. Her teaching methodology enhanced the learning process.


Vignesh Manikandan

The online classes were well-paced and helped us learn a ton of stuff within a short amount of time. Vaishali is very knowledgeable and handled all the sessions with outstanding professionalism. Thanks for your expertise


Darshan Gajjar

I learned a lot about Python, Numpy, Pandas, Visualization. The instructor, Swagat was excellent in explaining things clearly. The support team is also accommodative and resolves issues instantly.


Aashish Kumar

….. The faculty, Prashanth Nair, was extremely knowledgeable, and the entire class appreciated his way of teaching…..Support team was very accommodating and quick in providing responses. I was able to grab a 30% hike in my salary after getting certified.


Nikhil Lohakare

The sessions are very interesting and easy to understand. I enjoyed each and every one of them, thanks to the trainer, Prashant


C Muthu Raman

….. a brilliant platform to acquire new & relevant skills at ease. Well laid out course content and expert faculty ensure an excellent learning experience.


Surendaran Baskaran

The instructor is knowledgeable and shares their skills and knowledge. My learning experience has been outstanding with Simplilearn. The practice labs and materials are helpful for better learning. Thank you, Simplilearn. Happy Learning!!


Mukesh Pandey

….. an excellent platform for online learning. Their course curriculum is comprehensive and up to date. We get lifetime access to the recorded sessions in case we need to refresh our understanding. If you are looking to upskill….


Dastagiri Durgam

Incredible mentorship, and amazing and unique lectures. …..provides a great way to learn with self-paced videos and recordings of online sessions. …..


Shiv Sharma

Prashant Nair is an awesome faculty. The way he simplifies, relates and explains topics is outstanding. I would love to enroll for and attend all his classes.


Akash Raj

Technology Engineer

The instructor not only delivers the lecture but also focuses on practical aspects related to the subject. This is something about the course that really impressed me.


Shweta Chauhan

Thanks a lot, Sunny, for the immense support and guidance throughout the project, and for your patience while calmly helping me fix both small and big problems. You have excellent and in-depth knowledge about Python and the alternative options you taught me. I’m delighted to share my opinion about my experience.


Satabdi Adhikary

……courses are affordable and helped me learn something new during the lockdown. Moreover, I also got to add a Well-Known Global Name like Simplilearn to my resume. I could choose the trainer as well as enroll for multiple sessions using the Flexible Pass.


*Note: We reserve the right to revise/change any of the course content &/or instructor at our sole & absolute discretion, without prior notice to learner.

Course Features

  • Students 1 student
  • Max Students10000
  • Duration68 hour
  • Skill levelall
  • LanguageEnglish
  • Re-take course100000
  • Lesson 01 - Course Introduction

  • Lesson 02 - Introduction to Data Science

  • Lesson 03 - Python Libraries for Data Science

  • Lesson 04 - Statistics

  • Lesson 05 - Data Wrangling

  • Lesson 06 - Feature Engineering

  • Lesson 07 - Exploratory Data Analysis

  • Lesson 08 - Feature Selection


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