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Generative AI and Large Language Models with Python

Created By: Training Head

4.6 (10 Ratings) • 1 Students Enrolled

Requirements

Learners should have basic knowledge of Python programming and, preferably, some familiarity with machine learning concepts. A laptop or desktop with a stable internet connection is essential for participating in live sessions and hands-on practice. The program requires a commitment of 10–12 hours per week over 12 weeks, along with curiosity and enthusiasm for exploring AI technologies.

Course Description

The Generative AI & Large Language Models with Python program is a comprehensive, hands-on training designed to help learners master the cutting-edge technologies behind AI-powered text generation, chatbots, and intelligent assistants. Over 12 weeks, you’ll progress from Python essentials and Natural Language Processing fundamentals to advanced concepts like transformer architectures, Retrieval-Augmented Generation (RAG), and model fine-tuning using LoRA/PEFT techniques.
You’ll work with industry-leading tools such as Hugging Face, LangChain, OpenAI APIs, ChromaDB/FAISS, Streamlit, and Gradio, gaining practical skills through weekly labs, quizzes, and a final Capstone Project where you’ll build and deploy your own custom AI assistant.
This program blends online/offline live classes with project-driven learning to ensure you graduate ready to create real-world AI solutions.

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Generative AI and Large Language Models with Python

₹45,000.00
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Course Modules

Background

What you'll learn

End-to-End Learning

Hands-On Projects

Industry Tools

Practical AI Skills

Flexible Learning Modes

Core Career Benefits of
This Course

Designed to make you job-ready from day one.

Training Hours Comprehensive Learning Hours
Placement Live projects
Projects Placement Support & Career Guidance
Certifications Industry Recognized Certification
Career Benefits

Success Stories from
Previous Seminars

"Great Experience!"

Flexibility and the tools you get taught are top-notch; would love more depth in streamlit deployment.

Ankit Verma

Student / Professional

"Great Experience!"

Really liked using OpenAI APIs and hands-on experience in deploying custom assistants.

Shreya Malhotra

Student / Professional

"Great Experience!"

Live + offline sessions worked well; quiz-based assessments helped track my progress.

Rahul Patel

Student / Professional

"Great Experience!"

Instructor explained transformer architectures clearly, even for non-experts in ML.

Priya Nair

Student / Professional

"Great Experience!"

Good content overall, but weekly workload is heavy; would be tough for someone working full time.

Harish Khanna

Student / Professional

"Great Experience!"

12 weeks flew by — Python essentials to building AI assistants feels very job-relevant now.

Sonal Mehra

Student / Professional

"Great Experience!"

Model fine-tuning with LoRA/PEFT was eye-opening; I wish there were more examples in RAG.

Tanmay Gupta

Student / Professional

"Great Experience!"

The mix of theory (transformers, NLP) and tools (Streamlit, Gradio) is just perfect.

Neelima Joshi

Student / Professional

"Great Experience!"

Capstone project pushed me to apply everything; deployment section a bit fast though.

Vikram Dubey

Student / Professional

"Great Experience!"

Loved the hands-on labs with LangChain & HuggingFace, made tricky concepts super clear.

Aditi Rao

Student / Professional
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