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Generative AI Course

Live Interactive

VERIFIED

A Generative AI course introduces learners to AI models that create new content such as text, images, audio, and code. It covers foundational concepts, model architectures, and practical hands-on skills to build and apply generative tools in real-world scenarios.

Educator

Live

Classroom (Offline)

|

STARTS ON

15th Jun

|

DURATION

11 weeks

|

LANGUAGE

English / Hindi

BEST VALUE

Course Price

₹25,000₹25,000

Pay₹25,000

BEST VALUE

Course Price

₹25,000

Pay₹25,000

360+ Students Enrolled via Learnees

⚡24/7 Support by Learnees

1. Streamlit + Python Essentials

Topics:

Introduction to Python:variables datatype control structures
Functions modules error handling
Numpy and Pandas basics for data manipulation
Getting started with Streamlit
Using widgets layout and components
Creating interactive dashboards and LLM UI mockups

Hands-on:

Skills You Will Learn:

2. Machine Learning Foundations

Topics:

Understanding supervised and unsupervised learning
Scikit-learn model building: Linear & Logistic Regression
Train-test split cross-validation
Hyperparameter tuning and evaluation metrics

Hands-on:

Skills You Will Learn:

3. Deep Learning with PyTorch

Topics:

Neural network basics: perceptron multi layer networks
Introduction to PyTorch tensors and autograd
Building simple neural networks using nn.Module
Training loop with loss functions and optimizers
GPU acceleration and model evaluation

Hands-on:

Skills You Will Learn:

4. NLP Fundamentals

Topics:

Text: cleaning stemming lemmatization
Vectorization using Bag of Words TF-IDF Word2Vec
Sequence models: RNN LSTM concepts
Limitations of traditional NLP techniques

Hands-on:

Skills You Will Learn:

5. Transformers & Hugging Face

Topics:

Transformer architecture (self-attention encoder-decoder)
BERT GPT-2 overview and use cases
Using Hugging Face’s transformers pipeline
Downloading and using pre-trained models
Hands-on: sentiment classifier text summarizer

Hands-on:

Skills You Will Learn:

6. LangChain Essentials

Topics:

LangChain architecture:Chains Agents Memory
Building LLM chains using prompts and tools
reating a conversational bot with LangChain
Integration with OpenAI API
LangChain toolkits: calculator Python REPL

Hands-on:

Skills You Will Learn:

7. RAG with Hugging Face & LangChain

Topics:

Understanding RAG and how it enhances LLM's
Vector databases: FAISS Pinecone basics
Document loading and chunking for retrieval
Creating context-aware Q&A systems
Build a private chatbot using LangChain + RAG

Hands-on:

Skills You Will Learn:

8. Deployment & Optimization

Topics:

Prompt engineering patterns and anti-patterns
Using Streamlit Cloud and Hugging Face Spaces for deployment
Monitoring LLM behavior and optimization techniques
Caching
truncation rate limits and usage metrics
Addressing hallucinations bias and safety in LLMs

Hands-on:

Skills You Will Learn:

9. Capstone Project

Topics:

Plan and design a complete GenAI solution
Possible projects: Resume screener PDF-based chatbot AI tutor
Incorporate Streamlit + LangChain + RAG
Model evaluation and improvement
Presentation and deployment

Hands-on:

Skills You Will Learn:

516+ Selections

in JEE & Boards

10+ Years of

Coaching Excellence

4.1 Rated

by Students

Why Choose LEARNEES?

Need Guidance?

✓Compare Institutes

✓Discuss Fees & Scholarships

✓Career Counseling

Generative AI Course

3.5

4 Ratings|

✓

Verified

Batches and Timings

ON DEMAND

Flexible TimingAvailable

Online / Offline • Flexible time

On-Demand

SOLD OUT

Start From

JAN22

Batch

Online

10:00 AM10:00 AM (IST) • Duration: 11 weeks

MON - FRI

Weekday

₹25000.00

only

📅 Please select a batch timing to proceed with enrollment

Secure Transaction

360 Users Already Enrolled

First 3 Sessions - 100% Refund

What you'll learn in Generative AI Course

Course Specifications8

Python programming

Machine learning basics

Linear algebra

Data preprocessing

Deep learning fundamentals

Neural networks

Prompt engineering

Model evaluation and cloud computing basics.

Course Key Components10

TensorFlow

PyTorch

Keras

Hugging Face Transformers

OpenAI Playground

GitHub Copilot

Google Colab

Jupyter Notebook

LangChain

Stable Diffusion

Curriculum / Syllabus Overview By Experts

Master the skills employers are looking for with our comprehensive, hands-on curriculum

1

Streamlit + Python Essentials

6 Topics

2

Machine Learning Foundations

4 Topics

3

Deep Learning with PyTorch

5 Topics

4

NLP Fundamentals

4 Topics

5

Transformers & Hugging Face

5 Topics

Free Career Counselling

We're happy to help you 24/7

1. Streamlit + Python Essentials

Topics:

Introduction to Python:variables datatype control structures
Functions modules error handling
Numpy and Pandas basics for data manipulation
Getting started with Streamlit
Using widgets layout and components
Creating interactive dashboards and LLM UI mockups

2. Machine Learning Foundations

Topics:

Understanding supervised and unsupervised learning
Scikit-learn model building: Linear & Logistic Regression
Train-test split cross-validation
Hyperparameter tuning and evaluation metrics

3. Deep Learning with PyTorch

Topics:

Neural network basics: perceptron multi layer networks
Introduction to PyTorch tensors and autograd
Building simple neural networks using nn.Module
Training loop with loss functions and optimizers
GPU acceleration and model evaluation

4. NLP Fundamentals

Topics:

Text: cleaning stemming lemmatization
Vectorization using Bag of Words TF-IDF Word2Vec
Sequence models: RNN LSTM concepts
Limitations of traditional NLP techniques

5. Transformers & Hugging Face

Topics:

Transformer architecture (self-attention encoder-decoder)
BERT GPT-2 overview and use cases
Using Hugging Face’s transformers pipeline
Downloading and using pre-trained models
Hands-on: sentiment classifier text summarizer

6. LangChain Essentials

Topics:

LangChain architecture:Chains Agents Memory
Building LLM chains using prompts and tools
reating a conversational bot with LangChain
Integration with OpenAI API
LangChain toolkits: calculator Python REPL

7. RAG with Hugging Face & LangChain

Topics:

Understanding RAG and how it enhances LLM's
Vector databases: FAISS Pinecone basics
Document loading and chunking for retrieval
Creating context-aware Q&A systems
Build a private chatbot using LangChain + RAG

8. Deployment & Optimization

Topics:

Prompt engineering patterns and anti-patterns
Using Streamlit Cloud and Hugging Face Spaces for deployment
Monitoring LLM behavior and optimization techniques
Caching
truncation rate limits and usage metrics
Addressing hallucinations bias and safety in LLMs

9. Capstone Project

Topics:

Plan and design a complete GenAI solution
Possible projects: Resume screener PDF-based chatbot AI tutor
Incorporate Streamlit + LangChain + RAG
Model evaluation and improvement
Presentation and deployment

Why Choose LEARNEES

Discover the unique advantages that make our learning platform stand out

Academic Support

Expert guidance from top subject specialists
Daily doubt-clearing for zero concept backlog
1-on-1 mentorship with performance tracking

Exam-Focused Preparation

Structured & exam-aligned syllabus coverage
Targeted Previous Year Questions (PYQs) practice
Regular Mock Tests and All-India Test Series

Performance & Results

Detailed Performance Analysis
Rank Improvement Strategy
Time Management & Exam Strategy Sessions

Why enroll for Generative AI Course ?

Unlock your potential with Generative AI Course

Strong Foundation

Building a strong conceptual foundation early provides a decisive edge across all high-stakes competitive examinations. Mastering fundamental concepts through standard core curricula and foundational frameworks ensures long-term retention and flexible problem-solving.

Concept Clarity & Problem Solving

Master core concepts through structured learning, consistent practice, and detailed analysis of previous years' questions. Building strong analytical thinking and systematic problem-solving skills is essential for long-term success in any high-stakes competitive evaluation.

High Selection Opportunity

Starting early significantly increases your chances of selection into top-tier institutions and competitive positions. Consistent, long-term preparation yields superior rankings, greater flexibility, and outstanding career opportunities across any field.

Course Overview: Generative AI Course

Essential details: objectives, prerequisites, schedule, and outcomes

This course aims to equip learners with a solid understanding of generative AI concepts, models, and real-world applications. It enables participants to build, evaluate, and deploy generative models such as GPT, diffusion models, and VAEs. Learners will develop practical skills to create AI-driven content responsibly while understanding ethical, technical, and industry considerations.

Still have questions? Let's talk!

By:LEARNEES

₹625/ month

LIVE

Generative AI & Agentic AI Complete Course Vip Hills, Hyderabad

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Dur:6 months

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Explore More

Generative AI Course

Live Interactive

VERIFIED

A Generative AI course introduces learners to AI models that create new content such as text, images, audio, and code. It covers foundational concepts, model architectures, and practical hands-on skills to build and apply generative tools in real-world scenarios.

Educator

Live

Classroom (Offline)

|

STARTS ON

15th Jun

|

DURATION

11 weeks

|

LANGUAGE

English / Hindi

BEST VALUE

Course Price

₹25,000₹25,000

Pay₹25,000

BEST VALUE

Course Price

₹25,000

Pay₹25,000

360+ Students Enrolled via Learnees

⚡24/7 Support by Learnees

1. Streamlit + Python Essentials

Topics:

Introduction to Python:variables datatype control structures
Functions modules error handling
Numpy and Pandas basics for data manipulation
Getting started with Streamlit
Using widgets layout and components
Creating interactive dashboards and LLM UI mockups

Hands-on:

Skills You Will Learn:

2. Machine Learning Foundations

Topics:

Understanding supervised and unsupervised learning
Scikit-learn model building: Linear & Logistic Regression
Train-test split cross-validation
Hyperparameter tuning and evaluation metrics

Hands-on:

Skills You Will Learn:

3. Deep Learning with PyTorch

Topics:

Neural network basics: perceptron multi layer networks
Introduction to PyTorch tensors and autograd
Building simple neural networks using nn.Module
Training loop with loss functions and optimizers
GPU acceleration and model evaluation

Hands-on:

Skills You Will Learn:

4. NLP Fundamentals

Topics:

Text: cleaning stemming lemmatization
Vectorization using Bag of Words TF-IDF Word2Vec
Sequence models: RNN LSTM concepts
Limitations of traditional NLP techniques

Hands-on:

Skills You Will Learn:

5. Transformers & Hugging Face

Topics:

Transformer architecture (self-attention encoder-decoder)
BERT GPT-2 overview and use cases
Using Hugging Face’s transformers pipeline
Downloading and using pre-trained models
Hands-on: sentiment classifier text summarizer

Hands-on:

Skills You Will Learn:

6. LangChain Essentials

Topics:

LangChain architecture:Chains Agents Memory
Building LLM chains using prompts and tools
reating a conversational bot with LangChain
Integration with OpenAI API
LangChain toolkits: calculator Python REPL

Hands-on:

Skills You Will Learn:

7. RAG with Hugging Face & LangChain

Topics:

Understanding RAG and how it enhances LLM's
Vector databases: FAISS Pinecone basics
Document loading and chunking for retrieval
Creating context-aware Q&A systems
Build a private chatbot using LangChain + RAG

Hands-on:

Skills You Will Learn:

8. Deployment & Optimization

Topics:

Prompt engineering patterns and anti-patterns
Using Streamlit Cloud and Hugging Face Spaces for deployment
Monitoring LLM behavior and optimization techniques
Caching
truncation rate limits and usage metrics
Addressing hallucinations bias and safety in LLMs

Hands-on:

Skills You Will Learn:

9. Capstone Project

Topics:

Plan and design a complete GenAI solution
Possible projects: Resume screener PDF-based chatbot AI tutor
Incorporate Streamlit + LangChain + RAG
Model evaluation and improvement
Presentation and deployment

Hands-on:

Skills You Will Learn:

516+ Selections

in JEE & Boards

10+ Years of

Coaching Excellence

4.1 Rated

by Students

Why Choose LEARNEES?

Need Guidance?

✓Compare Institutes

✓Discuss Fees & Scholarships

✓Career Counseling

Generative AI Course

3.5

4 Ratings|

✓

Verified

Batches and Timings

ON DEMAND

Flexible TimingAvailable

Online / Offline • Flexible time

On-Demand

SOLD OUT

Start From

JAN22

Batch

Online

10:00 AM10:00 AM (IST) • Duration: 11 weeks

MON - FRI

Weekday

₹25000.00

only

📅 Please select a batch timing to proceed with enrollment

Secure Transaction

360 Users Already Enrolled

First 3 Sessions - 100% Refund

What you'll learn in Generative AI Course

Course Specifications8

Python programming

Machine learning basics

Linear algebra

Data preprocessing

Deep learning fundamentals

Neural networks

Prompt engineering

Model evaluation and cloud computing basics.

Course Key Components10

TensorFlow

PyTorch

Keras

Hugging Face Transformers

OpenAI Playground

GitHub Copilot

Google Colab

Jupyter Notebook

LangChain

Stable Diffusion

Curriculum / Syllabus Overview By Experts

Master the skills employers are looking for with our comprehensive, hands-on curriculum

1

Streamlit + Python Essentials

6 Topics

2

Machine Learning Foundations

4 Topics

3

Deep Learning with PyTorch

5 Topics

4

NLP Fundamentals

4 Topics

5

Transformers & Hugging Face

5 Topics

Free Career Counselling

We're happy to help you 24/7

1. Streamlit + Python Essentials

Topics:

Introduction to Python:variables datatype control structures
Functions modules error handling
Numpy and Pandas basics for data manipulation
Getting started with Streamlit
Using widgets layout and components
Creating interactive dashboards and LLM UI mockups

2. Machine Learning Foundations

Topics:

Understanding supervised and unsupervised learning
Scikit-learn model building: Linear & Logistic Regression
Train-test split cross-validation
Hyperparameter tuning and evaluation metrics

3. Deep Learning with PyTorch

Topics:

Neural network basics: perceptron multi layer networks
Introduction to PyTorch tensors and autograd
Building simple neural networks using nn.Module
Training loop with loss functions and optimizers
GPU acceleration and model evaluation

4. NLP Fundamentals

Topics:

Text: cleaning stemming lemmatization
Vectorization using Bag of Words TF-IDF Word2Vec
Sequence models: RNN LSTM concepts
Limitations of traditional NLP techniques

5. Transformers & Hugging Face

Topics:

Transformer architecture (self-attention encoder-decoder)
BERT GPT-2 overview and use cases
Using Hugging Face’s transformers pipeline
Downloading and using pre-trained models
Hands-on: sentiment classifier text summarizer

6. LangChain Essentials

Topics:

LangChain architecture:Chains Agents Memory
Building LLM chains using prompts and tools
reating a conversational bot with LangChain
Integration with OpenAI API
LangChain toolkits: calculator Python REPL

7. RAG with Hugging Face & LangChain

Topics:

Understanding RAG and how it enhances LLM's
Vector databases: FAISS Pinecone basics
Document loading and chunking for retrieval
Creating context-aware Q&A systems
Build a private chatbot using LangChain + RAG

8. Deployment & Optimization

Topics:

Prompt engineering patterns and anti-patterns
Using Streamlit Cloud and Hugging Face Spaces for deployment
Monitoring LLM behavior and optimization techniques
Caching
truncation rate limits and usage metrics
Addressing hallucinations bias and safety in LLMs

9. Capstone Project

Topics:

Plan and design a complete GenAI solution
Possible projects: Resume screener PDF-based chatbot AI tutor
Incorporate Streamlit + LangChain + RAG
Model evaluation and improvement
Presentation and deployment

Why Choose LEARNEES

Discover the unique advantages that make our learning platform stand out

Academic Support

Expert guidance from top subject specialists
Daily doubt-clearing for zero concept backlog
1-on-1 mentorship with performance tracking

Exam-Focused Preparation

Structured & exam-aligned syllabus coverage
Targeted Previous Year Questions (PYQs) practice
Regular Mock Tests and All-India Test Series

Performance & Results

Detailed Performance Analysis
Rank Improvement Strategy
Time Management & Exam Strategy Sessions

Why enroll for Generative AI Course ?

Unlock your potential with Generative AI Course

Strong Foundation

Building a strong conceptual foundation early provides a decisive edge across all high-stakes competitive examinations. Mastering fundamental concepts through standard core curricula and foundational frameworks ensures long-term retention and flexible problem-solving.

Concept Clarity & Problem Solving

Master core concepts through structured learning, consistent practice, and detailed analysis of previous years' questions. Building strong analytical thinking and systematic problem-solving skills is essential for long-term success in any high-stakes competitive evaluation.

High Selection Opportunity

Starting early significantly increases your chances of selection into top-tier institutions and competitive positions. Consistent, long-term preparation yields superior rankings, greater flexibility, and outstanding career opportunities across any field.

Course Overview: Generative AI Course

Essential details: objectives, prerequisites, schedule, and outcomes

This course aims to equip learners with a solid understanding of generative AI concepts, models, and real-world applications. It enables participants to build, evaluate, and deploy generative models such as GPT, diffusion models, and VAEs. Learners will develop practical skills to create AI-driven content responsibly while understanding ethical, technical, and industry considerations.

Still have questions? Let's talk!

By:LEARNEES

₹11,666/ month