Python Training in Bangalore

SKU: 10953
12 Lesson
|
40 Hours
igmGuru’s Python Training in Bangalore is the best place to learn one of the most popular programming languages used in software development and data science. This course covers everything from basic programming concepts and writing Python code to working with data, web development, and automation using Python. Our professional mentors, with over 15 years of industry experience, provide hands-on knowledge to help you build real-world skills.
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Python Training in Bangalore

Python Course in Bangalore Overview

Our Python course in Bangalore is designed to learn you Python from beginner to advanced level. You will learn how to work with libraries to handle data, build machine learning models and create data visualizations. We provide hands-on projects to help you practice and prepare for real-world challenges. Additionally, we offer job assistance with interview tips to help you become a Python developer.

Skills Covered in Python Training

  1. Learn the basics of Python programming
  2. Understand data analysis and statistics
  3. Work with Python libraries like Pandas, NumPy, and Matplotlib
  4. Learn machine learning using Scikit-Learn
  5. Build data visualizations
  6. Perform web scraping and integrate with Hadoop and Spark

Eligibility for Python Programming Classes in Bangalore

This course is great for anyone who wants to learn a programming language for a job in software development or data science. It is a good fit for:

  • Anyone who wants to learn programming
  • Software architects
  • Team leaders in tech
  • Software engineers
  • Software developers
  • People new to coding

Pre-requisites

  1. No advanced coding knowledge required
  2. Basic understanding of programming concepts is helpful but not mandatory

Why Learn Python?

  1. Suitable for both beginners and experienced professionals
  2. Opens up various job opportunities
  3. Offers a large collection of libraries and frameworks
  4. Easy-to-learn syntax makes it beginner-friendly
  5. Python is widely used in industries like data science, web development, automation, and machine learning

Job Roles After Completing the Course

  1. Python Developer
  2. Data Scientist
  3. Machine Learning Engineer
  4. Data Analyst
  5. Web Developer
  6. Automation Engineer

Benefits of Learning Python

  1. According to Emergen Research, the global market is expected to reach USD 100.6 million by 2030, growing at a CAGR of 44.8%.
  2. Python is ranked among the top 3 most popular programming languages in 2025(TIOBE Index).
  3. It is widely used in data science, machine learning, AI, web development, automation, and more.
  4. Python's simple syntax makes it a great first language for beginners while still powerful for experts.
  5. It has a huge ecosystem of libraries like Pandas, TensorFlow, Django, and Flask.

Key Features

Python Classes in Bangalore Modules

1. What is Python?
2. Installing Python
3. Python Syntax and Indentation
1. Data Science with Python
2. Introduction to Data Visualization
3. Processes in Data Science
4. Data Wrangling, Data Exploration, and Model Selection
5. Exploratory Data Analysis or EDA
6. Data Visualization
7. Plotting
8. Hypothesis Building and Testing
9. Data Scientists
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
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
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
1. SciPy and its Characteristics, SciPy sub-packages
2. SciPy sub-packages –Integration, SciPy sub-packages – Optimize
3. Linear Algebra
4. SciPy sub-packages – Statistics, SciPy sub-packages – Weave
5. SciPy sub-packages - I O
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
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
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
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
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
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
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1-800-7430-173 (US Toll Free)
+91 7240740740 (India)
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Python Course Fees in Bangalore

Online Class Room Program

US $ 599.00
100% Money Back Guarantee
  • Duration : 40 Hrs
  • Plus Self Paced

Classes Starting From

  • Fast Track Batch 04 Jun 2026
  • Weekday Batch 08 Jun 2026
  • Weekend Batch 06 Jun 2026

Corporate Training

Corporate Training
  • Customized Training Delivery Model
  • Flexible Training Schedule Options
  • Industry Experienced Trainers
  • 24x7 Support
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Want to know Today's Offer

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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

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