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Python Data Science Course

4.9 (218 Ratings)

This Python Data Science course enables you to master Data Science using Python. You will work on various Python libraries such as SciPy, NumPy, Matplotlib, Lambda function, etc. The Objective of the course is to make you proficient in Data Science and Python skills through real-world projects covering domains like retail, e-commerce, etc.

Ranked #1 Data Science Program by India TV

Key Highlights

39 Hrs Instructor Led Training
24 Hrs Self-paced Videos
50 Hrs Project & Exercises
Job Assistance
Flexible Schedule
Lifetime Free Upgrade
Mentor Support

Python Data Science Course Overview

What will you learn in this Python Data Science course?

  1. Introduction to Python for Data Science
  2. OOP concepts, expressions, and functions
  3. What is SQLite in Python? Operations and classes
  4. Creating Pig and Hive UDF in Python
  5. Deploying Python for MapReduce programming
  6. Real-world Data Science projects
  • BI Managers and Project Managers
  • Software Developers and ETL Professionals
  • Analytics Professionals
  • Big Data Professionals
  • Those who are wanting to have a career in this field

You don’t need any specific knowledge for this Data Science with Python course. Though, a basic knowledge of programming can help.

  • Python’s design and libraries provide 10 times more productivity compared to C, C++, or Java
  • A Senior Python Developer in the United States can earn US$102,000/year – Indeed

It is one of the best programming languages that is used for the domain of Data Science. Intellipaat is offering the definitive Python training for learning Python coding and running it on various systems such as Windows, Linux, and Mac, which makes it one of the highly versatile languages for the domain of Data Analytics. Upon the completion of this Data Science with Python course, you will be able to get the best jobs in the Data Science domain at top salaries.

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Data Scientist: The Sexiest Job of the 21st Century - Harvard Business Review
Data really powers everything that we do. - By Jeff Weiner, CEO of LinkedIn

Career Transition

55% Average Salary Hike

45 LPA Highest Salary

12000+ Career Transitions

300+ Hiring Partners

Career Transition Handbook

Skills Covered

Probability & Statistics

Machine Learning


Data Manipulation

Data Visualization with Matplotlib

OOPS in Python

Dimensionality Reduction

Time Series Forecasting

Python Integration with Spark

Pandas, NumPy, & Scikit-Learn

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Course Fees

Self Paced Training

  • 24 Hrs e-learning videos
  • Flexible Schedule
  • Lifetime Free Upgrade


Online Classroom Preferred

  • Everything in Self-Paced Learning, plus
  • 39 Hrs of Instructor-led Training
  • One to one doubt resolution sessions
  • Attended as many batches as you want for Lifetime
  • Job Assistance
22 Jan


08:00 PM TO 11:00 PM IST (GMT +5:30)

25 Jan


07:00 AM TO 09:00 AM IST (GMT +5:30)

29 Jan


08:00 PM TO 11:00 PM IST (GMT +5:30)

06 Feb


08:00 PM TO 11:00 PM IST (GMT +5:30)

16,017 10% OFF Expires in

Corporate Training

  • Customized Learning
  • Enterprise grade learning management system (LMS)
  • 24x7 Support
  • Enterprise grade reporting

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Python Data Science Course Curriculum

Live Course Self Paced

Module 01 - Introduction to Data Science using Python


1.1 What is Data Science, what does a data scientist do
1.2 Various examples of Data Science in the industries
1.3 How Python is deployed for Data Science applications
1.4 Various steps in Data Science process like data wrangling, data exploration and selecting the model.
1.5 Introduction to Python programming language
1.6 Important Python features, how is Python different from other programming languages
1.7 Python installation, Anaconda Python distribution for Windows, Linux and Mac
1.8 How to run a sample Python script, Python IDE working mechanism
1.9 Running some Python basic commands
1.10 Python variables, data types and keywords.

Hands-on Exercise – Installing Python Anaconda for the Windows, Linux and Mac

Module 02 - Python basic constructs


2.1 Introduction to a basic construct in Python
2.2 Understanding indentation like tabs and spaces
2.3 Python built-in data types
2.4 Basic operators in Python
2.5 Loop and control statements like break, if, for, continue, else, range() and more.

Hands-on Exercise

1.Write your first Python program
2. Write a Python function (with and without parameters)
3. Use Lambda expression
4. Write a class
5. Create a member function and a variable
6. Create an object and write a for loop to print all odd numbers

3.1 Introduction to mathematical computing in Python
3.2 What are arrays and matrices, array indexing, array math, Inspecting a NumPy array, NumPy array manipulation

Hands-on Exercise

1. How to import NumPy module
2. Creating array using ND-array
3. Calculating standard deviation on array of numbers and calculating correlation between two variables.

4.1 What is a data Manipulation. Using Pandas library
4.2 NumPy dependency of Pandas library
4.3 Series object in pandas
4.4 DataFrame in Pandas
4.5 Loading and handling data with Pandas
4.6 How to merge data objects
4.7 Concatenation and various types of joins on data objects, exploring dataset

Hands-on Exercise

1. Doing data manipulation with Pandas by handling tabular datasets that includes variable types like float, integer, double and others.
2. Cleaning dataset, Manipulating dataset, Visualizing dataset

5.1 Introduction to Matplotlib
5.2 Using Matplotlib for plotting graphs and charts like Scatter, Bar, Pie, Line, Histogram and more
5.3 Matplotlib API

Hands-on Exercise –

1. Deploying Matplotlib for creating pie, scatter, line and histogram.
2. Subplots and Pandas built-in data visualization.

6.1 Central Tendency
6.2 Variability
6.3 Hypothesis Testing
6.4 Anova
6.5 Correlation
6.6 Regression
6.7 Probability Definitions and Notation
6.8 Joint Probabilities
6.9 The Sum Rule, Conditional Probability, and the Product Rule
6.10 Bayes Theorem

Hands-on Exercise –

1. We will analyze both categorical data and quantitative data
2. Focusing on specific case studies to help solidify the week’s statistical concepts

7.1 Revision of topics in Python (Pandas, Matplotlib, NumPy, scikit-Learn)
7.2 Introduction to machine learning
7.3 Need of Machine learning
7.4 Types of machine learning and workflow of Machine Learning
7.5 Uses Cases in Machine Learning, its various algorithms
7.6 What is supervised learning
7.7 What is Unsupervised Learning

Hands-on Exercise

1. Demo on ML algorithms

8.1 What is linear regression
8.2 Step by step calculation of Linear Regression
8.3 Linear regression in Python

Hands-on Exercise – Using Python library Scikit-Learn for coming up with Random Forest algorithm to implement supervised learning.

9.1 Logistic Regression
9.2 What is classification
9.3 Decision Tree, Confusion Matrix, Random Forest, Naïve Bayes classifier (Self paced), Support Vector Machine(self paced), XGBoost (self paced)

Hands-on Exercise – Using Python library Scikit-Learn for coming up with Random Forest algorithm to implement supervised learning.

10.1 Introduction to unsupervised learning
10.2 Use cases of unsupervised learning
10.3 What is clustering
10.4 Types of clustering(self-paced)-Exclusive clustering, Overlapping Clustering, Hierarchical Clustering(self-paced)
10.5 What is K-means clustering
10.6 Step by step calculation of k-means algorithm
10.7 Association Rule Mining(self-paced), Market Basket Analysis(self-paced), Measures in association rule mining(self-paced)-support, confidence, lift
10.8 Apriori Algorithm

Hands-on Exercise

1. Setting up the Jupyter notebook environment
2. Loading of a dataset in Jupyter
3. Algorithms in Scikit-Learn package for performing Machine Learning techniques and training a model to search a grid.
4. Practice on k-means using Scikit
5. Practice on Apriori

11.1 Introduction to Dimensionality
11.2 Why Dimensionality Reduction
11.3 PCA
11.4 Factor Analysis
11.5 LDA

Hands-on Exercise – Practice Dimensionality reduction Techniques : PCA, Factor Analysis, t-SNE, Random Forest, Forward and Backward feature

12.1 White Noise
12.2 AR model
12.3 MA model
12.4 ARMA model
12.5 ARIMA model
12.6 Stationarity
12.7 ACF & PACF

Hands-on Exercise

1. Create AR model
2. Create MA model
3. Create ARMA model

13.1 Understanding the OOP paradigm like encapsulation, inheritance, polymorphism and abstraction
13.2 What are access modifiers, instances, class members
13.3 Classes and objects
13.4 Function parameter and return type functions
13.5 Lambda expressions.

Hands-on Exercise

1. Writing a Python program and incorporating the OOP concepts

14.1 Introduction to PySpark
14.2 Who uses PySpark, need of spark with python
14.3 PySpark installation
14.4 PySpark fundamentals
14.5 Advantage over MapReduce, PySpark
14.6 Use-cases PySpark and demo.

Hands-on Exercise –

1. Demonstrating Loops and Conditional Statements
2. Tuple – related operations, properties, list, etc.
3. List – operations, related properties
4. Set – properties, associated operations, dictionary – operations, related properties.

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Data Science with Python Projects

Peer Learning

Via Intellipaat PeerChat, you can interact with your peers across all classes and batches and even our alumni. Collaborate on projects, share job referrals & interview experiences, compete with the best, make new friends — the possibilities are endless and our community has something for everyone!


Python Data Science Course Certification

How can I get Python Data Science course certification?

To get the Python Data Science certification from Intellipaat, you are required to successfully complete the whole Data Science with Python course. Further, you need to execute all the given projects and assignments that are part of this course under the guidance of our expert trainers and score over 60 percent in our certification exam. After this, you will be rewarded with our course completion certificate recognized by top companies, including Mu Sigma, Ericsson, Cognizant, Cisco, TCS, Sony, etc.

Yes. Intellipaat’s Python Data Science certification is totally worth it. Data Science is one of the most sought-after career opportunities today, and Python is the most popular language that is used in the IT industry for coding and software development purposes.

Once you complete the Data Science with Python course program from Intellipaat and clear the examination, you will receive the course completion certificate through our LMS. This certification from Intellipaat has lifetime validity and is well-recognized by leading organizations across the world.

You will receive Intellipaat’s Data Science with Python certificate once you complete the training program with us and clear the certification exam with the help of our Learning Management System. After passing the exam conducted by Intellipaat, you will get access to downloading your Data Science with Python course completion certificate from the LMS, and you can share it with your potential employers through email or LinkedIn.

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Python Data Science Course Reviews

4.9 ( 3,191 )

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Python Data Science Course FAQs

What is Python for Data Science?

It is an open-source, high-level, interpreted programming language that offers an excellent approach to object-oriented programming. It is one of the most popular languages used by data scientists for a variety of projects and applications. Python has a lot of features for dealing with arithmetic, statistics, and scientific functions which will be helpful for data science-related tasks.

This language has always been a highly preferred choice of data scientists due to its well-known features such as simplicity, scalability, numerous libraries, and large community, among other things. It offers hundreds of libraries and frameworks in which most of which are focused on Data Analytics, Data Visualizations, Machine Learning, and many more, making it ideal for Data Science projects. Moreover, Python programs can easily replace the entire solution and save a lot of manual work.

When it comes to data science projects, either Python or R are the best options. However, if you want to explore further in Machine Learning and Artificial Intelligence fields, Python is the way to go. It is a strong and adaptable programming language that programmers use to accomplish a wide range of computer science tasks. Moreover, the scope for python is comparatively more than the R programming language.

Intellipaat’s Python training will give you hands-on experience in mastering one of the best programming languages, that is Python. In this online Data Science with Python course, you will learn about the basic and advanced concepts, including MapReduce, Machine Learning, Hadoop streaming, etc. and also packages such as Scikit and SciPy. You will be awarded Intellipaat’s course completion certificate after successfully completing this Python training.

As part of this online Data Science with Python course, you will be working on real-time projects that have high relevance in the corporate world, and the curriculum is designed by industry experts. Upon the completion of the Data Science with Python certification, you can apply for some of the best jobs in top MNCs around the world at top salaries. Intellipaat offers lifetime access to videos, course materials, 24/7 support, and course material upgrading to the latest version at no extra fees. Hence, it is clearly a one-time investment.

Yes, Intellipaat publishes various blogs on Data Science and Python. Among them, the major ones are Python for Data Science tutorial, Data Science Interview Questions, and Python Interview Questions.

At Intellipaat, you need not worry about missing a class. In the LMS, we provide recorded videos of each session so that learners can refer to it at any time. Our support team will also be available to assist you with any such concerns. So, if you miss any session, simply contact the support team. They will schedule an extra class for Python training and one-on-one meetings with your trainers to let you catch up.

Yes. This course does include one practice test that is created with the latest market trends and the actual examination syllabus in mind. This Python training also includes a sample test designed to help you prepare for the exam by providing you with an idea of the type of questions and the format in which they will be asked.

At Intellipaat, you can enroll in either the instructor-led online training or self-paced training. Apart from this, Intellipaat also offers corporate training for organizations to upskill their workforce. All trainers at Intellipaat have 12+ years of relevant industry experience, and they have been actively working as consultants in the same domain, which has made them subject matter experts. Go through the sample videos to check the quality of our trainers.

Intellipaat is offering 24/7 query resolution, and you can raise a ticket with the dedicated support team at any time. You can avail of email support for all your queries. If your query does not get resolved through email, we can also arrange one-on-one sessions with our support team. However, 1:1 session support is provided for a period of 6 months from the start date of your course.

Intellipaat is offering you the most updated, relevant, and high-value real-world projects as part of the training program. This way, you can implement the learning that you have acquired in real-world industry setup. All training comes with multiple projects that thoroughly test your skills, learning, and practical knowledge, making you completely industry-ready.

You will work on highly exciting projects in the domains of high technology, ecommerce, marketing, sales, networking, banking, insurance, etc. After completing the projects successfully, your skills will be equal to 6 months of rigorous industry experience.

Intellipaat actively provides placement assistance to all learners who have successfully completed the training. For this, we are exclusively tied-up with over 80 top MNCs from around the world. This way, you can be placed in outstanding organizations such as Sony, Ericsson, TCS, Mu Sigma, Standard Chartered, Cognizant, and Cisco, among other equally great enterprises. We also help you with the job interview and résumé preparation as well.

You can definitely make the switch from self-paced training to online instructor-led training by simply paying the extra amount. You can join the very next batch, which will be duly notified to you.

Once you complete Intellipaat’s training program, working on real-world projects, quizzes, and assignments and scoring at least 60 percent marks in the qualifying exam, you will be awarded Intellipaat’s course completion certificate. This certificate is very well recognized in Intellipaat-affiliated organizations, including over 80 top MNCs from around the world and some of the Fortune 500companies.

Apparently, no. Our job assistance program is aimed at helping you land in your dream job. It offers a potential opportunity for you to explore various competitive openings in the corporate world and find a well-paid job, matching your profile. The final decision on hiring will always be based on your performance in the interview and the requirements of the recruiter.

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