Python Course in Pune

12 Lesson

40 Hours

Add to Wishlist

igmGuru offers the best Python classes in Pune with the latest Python 3.12 version. This course covers popular libraries like Pandas, NumPy, and Matplotlib for data analysis, machine learning, and visualization. After completing the course, you will be ready for roles like Python Developer, Data Scientist, or Machine Learning Engineer.
Talk to our course experts today!

Enroll Now

Python Training in Pune Overview

Learn Python programming basics and advanced concepts in this Python course in Pune designed for beginners and professionals.

Understand key machine learning ideas to boost your career in this fast-growing field.

Get hands-on experience through real projects and exercises.

Learn from 15+ years of experienced trainers

Flexible learning options are available with online Python training in Pune for those who prefer remote classes.

Develop important skills in data manipulation, statistics, and creating clear visual reports using libraries.

We provide lifetime access to the study material and recorded sessions.

This Python training in Pune also offers help with resume building and interview preparation, and 100% placement guidance.

Our course is designed to provide both theoretical knowledge and practical exposure to become job-ready.

Recognized as one of the best Python classes in Pune for quality content, experienced trainers, and career support.

Work on the latest Python 3.12 version with performance and typing improvements

Key Features

Instructor Led Training : 40 Hrs
Experienced & Professional Trainers
Small Batches Upto 10 Participants
24 X 7 Lifetime Support & Access
1 On 1 Training Option Available
Flexible Schedule

Syllabus

Lesson 1 - Data Science Overview

1. Data Science

2. Data Scientists

3. Examples of Data Science

4. Python for Data Science

Lesson 2 - Data Analytics Overview

1. Introduction to Data Visualization

2. Processes in Data Science

3. Data Wrangling, Data Exploration, and Model Selection

4. Exploratory Data Analysis or EDA

5. Data Visualization

6. Plotting

7. Hypothesis Building and Testing

Lesson 3 - Statistical Analysis and Business Applications

1. Introduction to Statistics

2. Statistical and Non-Statistical Analysis

3. Some Common Terms Used in Statistics

4. Data Distribution: Central Tendency, Percentiles, Dispersion

5. Histogram, Bell Curve, Hypothesis Testing

6. Chi-Square Test, Correlation Matrix, Inferential Statistics

Lesson 4 - Python: Environment Setup and Essentials

1. Introduction to Anaconda

2. Installation of Anaconda Python Distribution - For Windows, Mac OS, and Linux

3. Jupyter Notebook Installation, Jupyter Notebook Introduction

4. Variable Assignment

5. Basic Data Types: Integer, Float, String, None, and Boolean; Typecasting

6. Creating, accessing, and slicing tuples

7. Creating, accessing, and slicing lists

8. Creating, viewing, accessing, and modifying dicts

9. Creating and using operations on sets

10. Basic Operators: 'in', '+', '*', Functions, Control Flow

Lesson 5 - Mathematical Computing with Python (NumPy)

1. NumPy Overview

2. Properties, Purpose, and Types of ndarray

3. Class and Attributes of ndarray Object

4. Basic Operations: Concept and Examples

5. Accessing Array Elements: Indexing, Slicing, Iteration, Indexing with Boolean Arrays

6. Copy and Views, Universal Functions (ufunc)

7. Shape Manipulation, Broadcasting, Linear Algebra

Lesson 6 - Scientific computing with Python (Scipy)

1. SciPy and its Characteristics, SciPy sub-packages

2. SciPy sub-packages â€“Integration, SciPy sub-packages â€“ Optimize

3. Linear Algebra

4. SciPy sub-packages â€“ Statistics, SciPy sub-packages â€“ Weave

5. SciPy sub-packages - I O

Lesson 7 - Data Manipulation with Python (Pandas)

1. Introduction to Pandas

2. Data Structures, Series, DataFrame, Missing Values

3. Data Operations, Data Standardization

4. Pandas File Read and Write Support

5. SQL Operation

Lesson 8 - Machine Learning with Python (Scikitâ€“Learn)

1. Introduction to Machine Learning

2. Machine Learning Approach

3. How Supervised and Unsupervised Learning Models Work

4. Scikit-Learn

5. Supervised Learning Models - Linear Regression, Logistic Regression

6. K Nearest Neighbors (K-NN) Model

7. Unsupervised Learning Models: Clustering, Dimensionality Reduction

8. Pipeline, Model Persistence, Model Evaluation - Metric Functions

Lesson 9 - Natural Language Processing with Scikit-Learn

1. NLP Overview

2. NLP Approach for Text Data

3. NLP Environment Setup

4. NLP Sentence analysis, NLP Applications

5. Major NLP Libraries, Scikit-Learn Approach

6. Scikit - Learn Approach Built - in Modules, Scikit - Learn Approach Feature Extraction

7. Bag of Words, Extraction Considerations

8. Scikit - Learn Approach Model Training

9. Scikit - Learn Grid Search and Multiple Parameters

10. Pipeline

Lesson 10 - Data Visualization in Python using Matplotlib

1. Introduction to Data Visualization

2. Python Libraries, Plots

3. Matplotlib Features: Line Properties Plot with (x, y), Controlling Line Patterns and Colors, Set Axis, Labels, and Legend Properties, Alpha and Annotation, Multiple Plots, Subplots

4. Types of Plots and Seaborn

Lesson 11 - Data Science with Python Web Scraping

1. Web Scraping

2. Common Data/Page Formats on The Web

3. The Parser, Importance of Objects

4. Understanding the Tree, Searching the Tree

5. Navigating options, Modifying the Tree

6. Parsing Only Part of the Document

7. Printing and Formatting, Encoding

Lesson 12 - Python integration with Hadoop, MapReduce and Spark

1. Need for Integrating Python with Hadoop

2. Big Data Hadoop Architecture

3. MapReduce, Cloudera QuickStart VM Set Up

4. Apache Spark

5. Resilient Distributed Systems (RDD)

6. PySpark, Spark Tools

7. PySpark Integration with Jupyter Notebook

Talk To Us

We are happy to help you

1-800-7430-173 (US Toll Free)

+91 7240740740 (India)

Drop Us a Query

Fields marked * are mandatory

Name

Phone Number

Comments

Request For Live Demo Class

Course Fees

Online Class Room Program

US $ 599.00

100% Money Back Guarantee

Duration : 40 Hrs
Plus Self Paced

Classes Starting From

Fast Track Batch 11 Jul 2026
Weekday Batch 13 Jul 2026
Weekend Batch 11 Jul 2026

Corporate Training

Customized Training Delivery Model
Flexible Training Schedule Options
Industry Experienced Trainers
24x7 Support

Trusted By Top Companies Worldwide

Want to know Today's Offer

Data Science with Python Certification Exam

Official certification exam name is Data Science with Python - Certified Associate (varies by provider)

Exam Format

Duration: 90 to 120 minutes
Number of Questions: 60–80
Passing Score: 65–70%
Type: Multiple-choice, multiple-response, and coding-based questions
Mode: Online (proctored) or in-person at certified centers

Exam Cost

Fee: $150 to $295 USD depending on certification provider

igmGuru provides a Course Completion Certificate for Data Science with Python Training. This certification validates your knowledge in Python for data analysis, visualization, and basic machine learning concepts. It also confirms your understanding of tools such as Pandas, NumPy, Matplotlib, and Scikit-learn used in data science projects. This certification can support roles such as Data Analyst, Junior Data Scientist, and Python Developer.

Data Science with Python Certification Exam

Reviews

Login

Email ID*

Password*

Forgot Password?

Python Course in Pune