From Beginner to Expert - Master
Generative AI in Big Classes! |
Generative AI |
in Big Classes!
A Career Transition program on Generative AI by Big Classes!
Duration
8 Weeks
Start Date
06 Jan 2025
Batch Details
- 4.5/5 Rating
- 1274 Learners
Course Highlights
- Comprehensive Curriculum: Covers essential topics in AI, machine learning, and generative AI, designed to build a strong foundational understanding.
- Hands-on Projects: Offers practical, project-based learning to help students apply theory to real-world scenarios.
- Expert Mentorship: Provides personalized guidance from industry professionals and AI experts, ensuring a deeper understanding of concepts.
- Job-Ready Skills: Focuses on skills and tools needed to excel in the AI industry, with placement assistance and career support.
- Cutting-Edge Tools: Teaches the latest AI frameworks and technologies such as TensorFlow, PyTorch, and NLP libraries.
- Flexible Learning: Offers both live sessions and recorded lectures to accommodate diverse learning schedules.
- Industry Collaboration: Partnerships with leading tech companies for job placements and internships, ensuring exposure to top-tier opportunities.
- Certifications: Awarding certificates that validate students’ proficiency in AI and generative AI, boosting employability.
Course Overview
The Generative AI Course at BigClasses provides a comprehensive introduction to cutting-edge AI technologies, focusing on generative models like GANs (Generative Adversarial Networks), VAEs (Variational Autoencoders), and transformers. Students will learn how to design, train, and deploy AI models for tasks such as image generation, text synthesis, and creative content creation. The course covers essential tools, including Python, TensorFlow, and PyTorch, while offering hands-on projects to develop practical skills. With expert mentorship and real-world applications, the course equips learners with the expertise needed to excel in the rapidly evolving field of generative AI.
Course Curriculum
Module 1 : Introduction to Python
Basics of Python Programming
Installation and Setup:
Installing Python and setting up a development environment (IDEs
like PyCharm, VSCode, Jupyter Notebooks)
Syntax and Basic Constructs:
- Variables and data types (integers, floats, strings, booleans)
- Basic input and output
- Comments and documentation
- Control Structures
Conditional Statements:
if, elif, else
Loops:
- for, while
- Loop control statements (break, continue, pass)
Functions
Defining Functions:
- Parameters and return values
Scope and Lifetime:
- Local and global variables
Lambda Functions:
- Anonymous functions
Module 2 : GenAI and It's Industry Applications
- Introduction to Generative AI
- AI vs ML vs DL vs NLP vs Generative AI
- Generative AI principles
- What is the role of ML in Gen-AI
- Different ML techniques (Supervised, Unsupervised, Semisupervised & Reinforcement Learning)
- Applications in various domains
- Ethical considerations
Module 3 : NLP & Deep Learning
- NLP essentials
● Basic NLP tasks
● Different text classification approaches
● Frequency based – Bag of words,TF-IDF, N-gram.
● Distribution Models – CBOW, Skipgram(Traditional approaches)and
word2vec, Glove.
● Ensemble Methods (Random Forest, Gradient Boosting, AdaBoost) &
Traditional Machine Learning Models – Naïve Bayes, Support Vector
Machine (SVM), Decision Trees, Logistic Regression.
● Deep learning techniques – CNNs, RNNs, LSTMs, GRU and
Transformers.
Module 4 : Generative AI Models
- Autoencodes
● VAE’s and applications
● GAN’s and it’s applications
● Different types of GAN’s and applications
Module 5 : Language Models & Transformer Models
- Different types of Language models
● Applications of Language models
● Transformers and its architecture
● BERT, RoBERTa, GPT variations
● Applications of transformer models
Module 6 : Prompt Engineering
- What is Prompt Engineering
● What are the different principles of Prompt Engineering
● Types of Different Prompt Engineering Techniques
● How to Craft effective prompts to the LLMs
● Priming Prompt
● Prompt Decomposition
Module 7 : Large Language Models
- Generative AI lifecycle
● What is RLHF
● LLM pre-training and scaling
● Different Fine-Tuning techniques
Module 8 : LLM's Embeddings
- What are word embeddings
● What is the use of word embeddings, where we can use it?
● Word Embeddings – Word2Vec, GloVe and FastText
● Contextual Embeddings – ELMo , BERT and GPT
● Sentence Embeddings – Doc2Vec, Infersent, Universal Sentence
Encoder
● Subword Embeddings – BPE(Byte Pair Encoding), Sentence Piece
● Usecase of Embeddings.
Module 9 : Different Chunk Metrics
- What is Chunking
● What is the use of chunking the document
● What are the traditional effective chunking techniques
● What are the problems and limitations with traditional chunking
techniques?
● How to overcome the limitations of Traditional chunking
● Advanced Chunking Techniques:
1. Character Splitting
2. Recursive Character Splitting
3. Document based Chunking
4. Semantic Chunking
5. Agentic Chunking
Module 10 : RAG and Advanced RA with Langchain
- What is RAG
● What are the main components of RAG
● High level architecture of RAG
● How to Build RAG using external data sources
● Advanced RAG
Module 11 : Langchain for LLMs
- What is Langchain
● What are the core concepts of Langchain
● Components of Langchain
● How to use Langchain agents
Module 12 : Vector Databases
- LlamaIndex
● What are Vector Databases
● Why do we prefer Vector Databases over Traditional Databases
● Different Types of Vector Databases: OpenSource and Close Source
● OpenSource: Chroma DB, Weaviate,Faiss,Qdrant
● Close-Source Vector Databases:Pinecone,ArangoDB,Cloud-Based
Solutions
Module 13 : Finetuning LLMs
- Supervised Finetuning
● Repurposing-Feature Extraction
● Advanced techniques in Supervised Finetuning -PEFT -LoRA, QLoRA
Module 14 : LLMs Evaluation
Text based LLMs
Automatic Evaluation: BULE Score, ROUGE Score, METEOR, BERT
Score.
Human Evaluation: Coherence, Factuality, Originality, EngagementImage based LLMs
Automatic Evaluation: Pixel-level metrics, FID (Frechet Inception
Distance), IS (Inception Score), Perceptual Quality Metrics,
Diversity Metrics.
Human Evaluation: Photorealism, Style, Creativity, CohesivenessAudio generation LLMs
Automatic Evaluation:FAD (Frechet Audio Distance),
IS (Inception Score),
Perceptual Quality Metrics – PAQM,
PAQM – SNR (Signal-to-Noise Ratio),
PAQM – PESQ (Perceptual Evaluation of Speech Quality)
Human Evaluation:Perceptual Quality – PQ,
PQ- Naturalness,
PQ-Fidelity,
PQ- Musicality,
Task Specific Evaluation.
Video Generation LLMs
Automatic Evaluation: FVD (Frechet Video Distance), Inception
Score(IS), Perceptual Quality Metrics, Motion Based Metrics –
Optical Flow Error, Content-Specific Metrics.
Human Evaluation: Visual Quality, Temporal Coherence, Content
Fidelit.
Module 15 : LLMops
Model Deployment and Management
Scalability and Performance Optimization
Security and Privacy
Monitoring and Logging
Cost Optimization
Model Interpretability and Explainability.
Module 16 : LLM's on Cloud
- Amazon Bedrock, Azure OpenAI
Module 17 : Different AI Tools
- ChatGPT, Gemini, Copilot
Free Career Counselling
We are Happy to help you 24/7
Key Tools
Hands on AI Projects
Core Banking Web Application
AI-Based Face Detection and Swapping System
Application Integration & Deployment
Data Ingestion, Preprocessing, Model Development & Training
Model Testing on Continuous Data & Improvement
Deep Learning in Dental Healthcare
Our Trainers
- Mr. Bhanu
- Lead Data Scientist & Gen AI Consultant
- 4.5+ Years of Experience of Industry Experience
- About the Tutor
- Our trainer is a Lead Data Scientist specializing in Generative AI and Prompt Engineering, with expertise in LLMs like Llama2. Over 10 years of experience in data science, focusing on predictive modelling, data preprocessing, NLP, and ML. She is a Generative AI industry expert and seasoned lead trainer, adept at shaping students’ careers by leveraging real-world scenarios in Data Science and Generative AI.
- Mr. Varun
- AI Engineer
- 4.5+ Years of Experience of Industry Experience
- About the Tutor
- Varun Thati is an AI and Software Engineer with 4.5+ years of experience specializing in Machine Learning, Generative AI, and Multi-Agent Systems. He is proficient in Python, NLP, Deep Learning, and AI-driven automation, with expertise in frameworks like TensorFlow, PyTorch, and FastAPI. Varun has developed and deployed AI-powered automation tools, customer support solutions, and predictive analytics systems using LLMs such as GPT and Gemini. He has strong experience in building scalable AI solutions, optimizing database performance, and developing robust APIs for AI integration. Passionate about Agentic AI, he continues to explore cutting-edge AI advancements to optimize workflows and drive innovation.
Generative Ai Training in Hyderabad Certifications
The Generative AI offered by BigClases.ai Institute holds meaningful importance in today’s technological environment. This certification signifies a complete understanding and practical skill in the field of Generative Ai, a technology with increasing importance across different industries.
Our Generative Ai Certification BigClasses Ai Institute not only validates foundational knowledge in Ai and machine learning but also show specialized expertise in generative models like GANs and VAEs. With BigClases Ai Institute certification, individuals not only improve their career opportunities but also gain the confidence to apply Generative Ai in solving real-time challenges responsibly and ethically.
Placement Assistance
Comprehensive Job Assistance
- Mastering the course
- Hackathons and Mock-Interviews with SMEs
- Quizzes and Assignments
- Portfolio Building with SMEs Assistance
- Resume Review
Student Testimonials
BigClasses' Generative AI Training was outstanding! The course covered everything from the basics to advanced concepts with hands-on practice. I feel confident applying AI techniques in my work now
The training was comprehensive and practical. BigClasses made learning generative AI easy and enjoyable, with excellent instructors and real-world applications. Highly recommended!
BigClasses helped me understand generative AI like never before! The content was clear, and the hands-on projects gave me the skills I needed for real-world AI applications.
BigClasses offers the best Generative AI Training! The course was well-structured, informative, and full of practical exercises. It boosted my career and deepened my AI knowledge.
Course FAQs
Can I take this course if I don't have much experience in coding or Ai
Yes, you can take this course even with limited coding or AI experience! The course is designed to start with foundational concepts, making it beginner-friendly. While some basic programming knowledge (like Python) is helpful.
What is Generative AI and Why this course in BigClasses?
Generative AI is a subset of artificial intelligence that creates new content, such as text, images, audio, or video, by learning patterns from existing data. Using models like GANs, autoencoders, or large language models (e.g., GPT), it powers applications in art, chatbots, gaming, and other creative or problem-solving domains.This Generative AI course at BigClasses stands out for its comprehensive curriculum, expert-led instruction, and practical, hands-on approach. Designed for all levels, it covers fundamental to advanced topics, emphasizing real-world applications. With personalized mentorship, industry-relevant projects, and access to cutting-edge tools, learners gain valuable skills to excel in AI-driven careers.
What is the cost generative Ai course Online?
Can I access the course materials after I finish the course?
Yes, you can access the course materials after completing the Generative AI course at BigClasses.
How experienced are instructors of BigClasses?
Instructors at BigClasses are highly experienced professionals with expertise in their respective fields. Many instructors also hold advanced degrees and certifications in AI, data science, and related technologies.
Are there any hands-on projects in the course to apply what I've learned?
Yes, the Generative AI course at BigClasses includes hands-on projects to help you apply what you’ve learned. These projects are designed to provide practical experience in areas such as creating AI-generated content, coding, building chatbots, and implementing advanced models like GANs and autoencoders.
Is there any support for job placement or internships after completing the course?
Is NLP part of generative AI?
Yes, Natural Language Processing (NLP) is a key component of Generative AI. In generative models, NLP techniques are used to generate and understand human language. Generative AI in NLP involves tasks like language generation, text completion, summarization, and sentiment analysis, making it a crucial area for AI applications in communication and content creation.
Can generative AI write code?
Yes, Generative AI can write code! Models like OpenAI’s Codex (which powers tools like GitHub Copilot) are specifically trained to generate code based on natural language prompts. They can assist in writing, completing, or debugging code in various programming languages like Python, JavaScript, and more.
