Upcoming Batches
| AI Online Training | 1-December-2025 | 8:00 am | Enroll |
About Course
Why Choose OnlineITvidhya for Gen AI Online Training?
OnlineITvidhya stands out as a trusted platform for Gen AI Online Training because of its industry-oriented curriculum, expert trainers, and hands-on learning experience. Our program focuses on real-time projects, practical applications, and job-ready skills that help learners master the rapidly expanding field of Generative AI. With personalized mentoring, flexible schedules, and high-quality learning resources, we ensure you gain the confidence and expertise needed to work on cutting-edge AI technologies.
How Will Generative AI Advance Your Career?
- Generative AI is transforming industries such as IT, healthcare, finance, marketing, design, and more. Learning Generative AI empowers you to:
- Work on next-gen technologies like LLMs
- Prompt engineering
- AI automation, and intelligent agents.
- Boost your career opportunities with high-demand roles such as AI Engineer, Prompt Engineer, Data Scientist, Machine Learning Engineer, and GenAI Application Developer.
- Stand out in the competitive job market with cutting-edge skills valued by top companies.
- Build AI-driven applications that enhance creativity, productivity, and business innovation.
- With the right Generative AI Online Training, you gain a future-proof skill set that opens doors to exciting and high-paying career paths.
Who Can Learn This Course?
- The Generative AI Online Training program is designed for learners from diverse backgrounds. You can join this course if you are:
Aspiring AI/ML professionals - Software developers or IT professionals
- Data analysts or data scientists
- Students or recent graduates seeking a career in AI
- Working professionals wanting to upskill
- Non-technical professionals interested in AI-driven workflows (with basic computer skills)
- Whether you’re a beginner or an experienced professional, our structured training helps you learn at your own pace.
What Are the Prerequisites?
There are no strict prerequisites to learn Generative AI, but having the following will help:
- Basic understanding of Python programming
- Fundamental knowledge of machine learning (optional but beneficial)
- Curiosity to explore AI technologies
- Analytical and problem-solving mindset
Don’t worry—if you’re new to AI, our trainers will guide you from the basics to advanced concepts.
Placement Assistance from OnlineITvidhya
At OnlineITvidhya, we provide dedicated placement support to help you land your dream role in the Generative AI ecosystem. Our placement assistance includes:
- Resume building and portfolio preparation
- Mock interviews with industry experts
- Real-world project guidance to showcase your skills
- Interview scheduling with top companies
- Job alerts and continuous support until you get placed
Curriculum
- 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, Semi-supervised & Reinforcement Learning).
- Applications in various domains.
- Ethical considerations.
- 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.
- Autoencoders.
- VAE’s and applications.
- GANs and it’s applications.
- Different types of GANs and applications.
- Different types of Language models
- Applications of Language models
- Transformers and its architecture
- BERT, RoBERTa, GPT variations
- Applications of transformer models
- 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
- Generative AI lifecycle
- What is RLHF
- LLM pre-training and scaling
- Different Fine-Tuning techniques
- 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.
- 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:
- Character Splitting
- Recursive Character Splitting
- Document based Chunking
- Semantic Chunking
- Agentic Chunking
- 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
- What is Langchain
- What are the core concepts of Langchain
- Components of Langchain
- How to use Langchain agents
- 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
- Supervised Finetuning
- Repurposing-Feature Extraction
- Advanced techniques in Supervised Finetuning -PEFT -LoRA, QLoRA
- Text based LLMs:
- Automatic Evaluation: BULE Score, ROUGE Score, METEOR, BERT Score.
- Human Evaluation: Coherence, Factuality, Originality, Engagement
- Image based LLMs:
- Automatic Evaluation: Pixel-level metrics, FID (Frechet Inception Distance), IS (Inception Score), Perceptual Quality Metrics, Diversity Metrics.
- Human Evaluation: Photorealism, Style, Creativity, Cohesiveness
- Audio 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, PQFidelity, 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.
- Model Deployment and Management
- Scalability and Performance Optimization
- Security and Privacy
- Monitoring and Logging
- Cost Optimization
- Model Interpretability and Explainability.
- Amazon Bedrock, Azure OpenAI
- Chatgpt, Gemini, google Notebook LM, Copilot, Grok, mid journey, ideogram, Jasper, Copy.ai, Notion AI, DALL·E, Midjourney, Stable Diffusion
Features
Lifetime Access
You will be provided with lifetime access to presentations, quizzes, installation guides and notes.
Assessments
After each training module there will be a quiz to assess your learning.
24*7 Support
We have a lifetime 24*7 Online Expert Support to resolve all your Technical queries.
Forum
We have a community forum for our learners that facilitates further learning through peer interaction and knowledge sharing.
Certificate
After successfully complete your course OnlineITvidhya will give you course completion Certificate.
Mock Interviews
Explore what the real-time interviews expect from you.
Reviews
Priya K
The AI Online Training from OnlineITvidhya was incredibly well-structured and hands-on. I appreciated the real-time projects, which helped me understand complex concepts like neural networks and NLP with ease. The trainer made AI approachable for a non-tech background like mine. Highly recommended!
Rahul
This AI training gave me the skills and confidence to transition into a data science role. The instructor explained every concept clearly and the support team was always available. The course covered everything from Python to deep learning. A great investment in my career!
Sneha
As someone new to AI, I found the training extremely beginner-friendly. The sessions were interactive, the examples were relevant, and the learning pace was perfect. The certification also added great value to my resume.
