Python Classes in Hyderabad

SKU: 10954
12 Lesson
|
40 Hours
Sign up for Python Classes in Hyderabad to build workplace-ready skills quickly and confidently. Gain hands-on experience that helps you stand out and grow in a competitive job market.

Python Course in Hyderabad Overview

Prerequisites

  • Basic understanding of programming logic and problem solving

Skills You Will Gain

  • Apply the language to data analysis and automation tasks
  • Test and optimize code for reliability and performance
  • Write clean, efficient scripts to automate everyday tasks

Key Features

Python Institute in Hyderabad Modules

1. What is Python?
2. Installing Python
3. Python Syntax and Indentation
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
8. Data Science with Python
9. Processes in Data Science
10. 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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Python Course Fees in Hyderabad

Online Class Room Program

₹35,940.00
100% Money Back Guarantee
  • Duration : 40 Hrs
  • Plus Self Paced

Classes Starting From

  • Fast Track Batch 28 Aug 2026
  • Weekday Batch 31 Aug 2026
  • Weekend Batch 29 Aug 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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