Python Programming Live Training Course ( Weekend Batch) Day 2

Python Programming Live Training Course

(Learn Python from Scratch — Syntax, Data Structures, Functions & File Handling with Real-Time Projects)

This comprehensive program provides hands-on training in Python programming, statistics, data analysis, data visualization, SQL, machine learning, deep learning, NLP, Generative AI, Large Language Models (LLMs), prompt engineering, RAG, AI agents, and real-world AI application development.

Learners will gain practical expertise in building end-to-end data science and machine learning solutions, including data preprocessing, feature engineering, exploratory data analysis, model development, model evaluation, deployment, and intelligent AI-powered applications.

The program includes real-time implementation of machine learning and Generative AI projects, helping students develop practical experience with LLM applications, RAG pipelines, vector databases, prompt engineering, AI agents, chatbot development, API integration, and production-ready AI workflows.

By the end of this training, learners will have strong expertise in Full Stack Data Science, Machine Learning, and Generative AI development, complete real-world projects for professional portfolios, and the confidence to pursue roles such as Data Scientist, Machine Learning Engineer, AI Engineer, Generative AI Engineer, and Data Analyst across modern technology-driven organizations.

Sample Videos:

Python Programming Live Training Course – Live Training – Demo Recording

Python Programming Live Training Course – Live Training – Day 1 Recording

Live Sessions Price:

For LIVE sessions – Offer price after discount is 90 ~~USD 65 ~~USD~~~~ 49 USD Or 8000~~INR 5500 INR~~ 3,500 Rupees

Enroll For Free Demo

Free Demo On:

Indian Timings: 3rd October @ 7 PM – 8 PM (IST)/

U.S Timings: 3rd October @ 9:30 AM – 10:30 AM (EST)/

U.K Timings: 3rd October @ 2:30 PM – 3:30 PM (BST)

Class Schedule:

For Participants in India: Saturday & Sunday @ @ 7 PM – 8 PM (IST)

For Participants in the US: Saturday & Sunday @ 9:30 AM – 10:30 AM (EST)

For Participants in the UK: Saturday & Sunday @ 2:30 PM – 3:30 PM (BST)

What students have to say about Sastik:

⭐ Sai Sastik Sir has deep knowledge of Data Science, Machine Learning, and Generative AI. The way he explained complex topics like Deep Learning, NLP, LLMs, and RAG was very clear and easy to understand. The hands-on projects were extremely valuable. — Rahul

⭐ Very supportive trainer with excellent industry knowledge. Sai Sastik Sir explained every concept step-by-step and gave practical guidance throughout the program. The Generative AI and AI Agents sessions were especially useful and informative. — Priya

⭐ One of the best learning experiences I have had in Data Science. Sai Sastik Sir explained Python, Machine Learning, Deep Learning, and Generative AI with real-world use cases. The practical projects helped me gain confidence in building AI applications. — Arjun

⭐ Sai Sastik Sir is an excellent trainer with strong knowledge of modern AI technologies. The sessions were interactive, practical, and easy to follow. His explanations of LLMs, Prompt Engineering, RAG, LangChain, and AI Agents were very helpful. — Sneha

⭐ Sai Sastik Sir is an excellent trainer with strong knowledge of Data Science, Machine Learning, and Generative AI. The concepts were explained clearly with practical examples and real-time projects. The hands-on sessions were very useful and helped me build confidence in developing AI solutions. — Vikram

What will I learn by the end of this course?

•Write clean Python code and work with real datasets
•Use Pandas & NumPy for data wrangling and analysis
•Apply statistical foundations to real-world problems
•Build, tune and evaluate Machine Learning models
•Design deep learning architectures (ANN, RNN, LSTM)
•Implement NLP pipelines and text classification
•Work with Transformers and Large Language Models (LLMs)
•Build RAG systems using LangChain & LlamaIndex
•Engineer effective prompts with Few-Shot & Chain-of-Thought
•Deploy autonomous AI Agents with Agentic AI frameworks
•Use open-source LLMs — LLaMA, Mistral, Gemma via Hugging Face
•Build intelligent chatbots and real-world AI applications

Salient Features:

60+ Hours of Live Training along with recorded videos
1 Year Access to the recorded videos
Course Completion Certificate

Who can enroll for this course?

🎓 Students & Fresh Graduates looking to build a career in Data Science, Machine Learning, and AI.
•💻 Software Developers who want to transition into AI, Machine Learning, and Generative AI roles.
•📊 Data Analysts seeking to upgrade their skills and become Data Scientists or AI Engineers.
• 🧪 Test Engineers & QA Professionals interested in AI-powered testing and intelligent automation.
•☁️ DevOps Engineers, SREs & IT Professionals looking to leverage AI in modern software systems.
•📈 Business Analysts who want to use data-driven insights and AI solutions for decision-making.
•🤖 Professionals interested in GenAI, LLMs, Prompt Engineering, RAG, and AI Agent Development.
•🚀 Working Professionals planning a career switch into the rapidly growing AI and Data Science domain.
•👨‍💼 Entrepreneurs & Startup Founders who want to build AI-powered products and business solutions.
•🔍 Anyone with basic computer knowledge who wants to learn Data Science and AI from beginner to advanced level.

Course syllabus:

Module 01: Python Programming

◆ Foundation

○ Introduction to AI
○ Definition and Scope
○ Introduction to Programming
○ Google Colab Setup
○ Why Python?

◆ Python Basics

○ Data Types & Type Conversion
○ Variables
○ Operators — Arithmetic, Comparison, Logical, Assignment, Membership, Identity, Bitwise
○ If-else & Nested If-else
○ For Loops & While Loops
○ Break, Continue and Pass

◆ Strings

○ Multiline Strings
○ String Patterns
○ Zero Padding
○ F-strings & Performance vs format()
○ String Functions: strip(), split(), join(), capitalize(), lower(), title(), upper(), istitle(), replace()

◆ Lists

○ List Creation & Retrieval
○ Item Replacement
○ List Comprehension & Mutable Concept
○ Nested Lists
○ List Functions: len(), append(), pop(), insert(), remove(), sort(), reverse()
○ Forward & Backward Indexing
○ Forward, Backward & Step Slicing

◆ Sets & Tuples

○ Sets — Creation, union(), intersection(), difference(), add(), remove(), pop()
○ Tuples — Creation & Immutable Concept
○ Tuple Concatenation & Unpacking
○ Tuple Functions: len(), count(), index(), sorted(), zip()

◆ Dictionaries

○ Dictionary Creation
○ Keys & Values Concept
○ Creating CSV from Python Dictionary
○ Dictionary Functions: keys(), values(), items(), get(), pop(), update(), from_dict(), zip(), clear(), map()

◆ Functions

○ Inbuilt vs User Defined Functions
○ Types of Function Arguments
○ Global vs Local Variables
○ Anonymous Function (Lambda)

◆ File Handling

○ Read Mode
○ Write Mode
○ Append Mode

Module 02: Python Libraries — Pandas & NumPy

◆ Pandas Introduction

○ Series — Creating, Empty Series, Series from List/Array/Column
○ Index in Series & Accessing Values
○ Statistical Operations on Series
○ NaN Values
○ Values, index, dtypes, size
○ Python List vs NumPy Array vs Pandas Series

◆ Series Functions

○ head()
○ tail()
○ sum()
○ count()
○ nunique()
○ sort_values()
○ value_counts()

◆ DataFrames

○ Creating DataFrames from Lists, Dictionaries & Arrays
○ Creating DataFrames from CSV, Excel & Other File Formats
○ DataFrame Attributes: shape, size, dtypes, index, columns
○ DataFrame Methods: head(), tail(), info(), describe()
○ Accessing and Modifying Data: loc, iloc
○ Adding and Dropping Columns and Rows
○ Renaming Columns and Index
○ Identifying Missing Data
○ Handling Missing Data: fillna(), dropna()
○ Replacing Values
○ Filtering Data
○ Sorting DataFrames
○ Applying Functions: apply(), map()
○ Grouping Data: groupby()
○ Merging and Joining DataFrames
○ Concatenating DataFrames
○ Setting and Resetting Index
○ MultiIndex (Hierarchical Indexing)

◆ Data Analysis with Pandas

○ Mathematical and Statistical Operations
○ Aggregation Methods: sum(), mean(), count(), nunique()
○ Pivot Tables and Cross-tabulations
○ Transpose of a DataFrame
○ Inplace Parameter & Ampersand (&) Logical Operator

◆ NumPy

○ Importance in Data Science
○ Creating NumPy Arrays from Lists and Tuples
○ arange(), linspace(), logspace()
○ zeros(), ones(), full()
○ Random Numbers: random(), rand(), randn(), randint()
○ Array Attributes: shape, size, ndim, dtype, itemsize
○ Array Manipulation, Mathematical Operations, Indexing & Slicing
○ NumPy Functions: add(), subtract(), multiply(), divide(), arange(), log(), abs(), reshape(), ravel(), flatten()
○ Statistics: mean(), median(), std(), sum(), min(), corrcoef(), cov()
○ List vs Array Performance Comparison
○ Diagonal, Trace & Identity Matrix
○ Multiplicative Inverse, Determinant & Adjoint Matrix
○ Parsing, Adding and Subtracting Matrices

FAQ’s – Python ProgrammingLive Training Course

1. When is free demo session?
The free demo is on Saturday, September 26th, 2026 at 8 PM IST. Register via the Google Form or WhatsApp link to receive the session link.

2. Who can enroll in this course?
Students, freshers, data analysts, software developers, working professionals, and anyone interested in Data Science, Machine Learning, and Generative AI can enroll.

3. Will class recordings will availabe?
Session recordings and materials will be shared so you can revise at your own pace if you miss a live session.

4. Will I Receive a Certificate?
Yes! Upon completing the program, you will receive a certificate of completion which you can add to your resume and LinkedIn profile.

5. What is the fees for this course?
The course fee is ₹3,500 (or 49 USD for international learners) for the full 15+ hour live program.

How can I enroll for this course?

Enroll For Free Demo

For any other details, Call me or Whatsapp me on +91-9133190573

For LIVE sessions – Offer price after discount is 90 ~~USD 65 ~~USD~~~~ 49 USD Or 8000~~INR 5500 INR~~ 3,500 Rupees

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Python Programming Live Training Course ( Weekend Batch) Day 2

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