Learn AI with Anand 4-week Live Cohort

Learn AI with Anand 4-week Live Cohort 
Mastering Multi-Agentic AI Frameworks 
(Course Code : MMAAI)
20-Hour course spread over 8 sessions.  Commencing 9th Sep 2025,  Timing: 07.30pm to 10.00pm IST during every Tuesdays & Thursdays for 4-weeks. Please write to [email protected] to book your spot.
Get a complimentary prerequisite module of 25+ hour course recordings of LLM Architecture, Transformers Building Blocks, Encoder only applications, Encoder-Decoder based applications, GenAI Inference, LLM + RAG configurations
Enquiry for Recorded Course: MTM-LLM, MViTM, MMAAI 
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Mastering Transformer Models for Computer Vision & Multimodal LLMs: MViTM
Session-1: Introduction to Vision Transformers (ViT) , Overview of Transformers in NLP vs. Computer Vision
Session-2: Vision Transformer Architecture, Image tokenization: Patching and embedding, Multi-Head Self-Attention in Vision
Session-3: Transfer learning in ViT models, Fine-tuning a pre-trained ViT model using PyTorch
Session-4: Object detection using Vision Transformers (e.g., DETR), Inference & Fine-Tuning RF-DETR Model using Super Vision and Roboflow
Session-5: Zero-Shot Object Detection using Self-Supervised DINO Architecture, DINO for Auto Labeling
Session-6: Segment Anything Model (SAM) - Model Inference, Fine-Tuning SAM using Super Vision and Roboflow 
Session-7: CLIP (Contrastive Language–Image Pre-training): Zero-Shot Image Classification using CLIP, CLIP as a Building block in Stable Diffusion
Session-8: Stable Diffusion Architecture, Variational Autoencoder (VAE), U-Net & Text Encoders for Image Generation & Neural Style Transfer applications.
MMAAI Course Outline
Session-1: Introduction to AI Agents, AI Agents Vs Agentic AI, Popular Frameworks, Creating a simple conversational & Data Analysis Agent using LangChain and PyDanticAI
Session-2: Introduction to LangGraph, Defining Node Functions, Creating Tools & Building Workflows, Use case with LangGraph: Customer Support Agent, Travel Planing Agent
Session-3: Introduction to  Crew Multi Agentic AI framework, Building a Multi-Agentic AI System using CrewAI.
Session-4: Introduction to AutoGen Framework, Building a Multi-Agentic AI System using AutoGen
Session-5: Building Multi-Agentic RAG System using Agno Framework with Claude Sonnet Reasoning & creating interactive Web Interface using Streamlit
Session-6: Introduction to MCP, Key Components of MCP architecture, Setting up MCP Servers, Building Functional AI using MCPs, Use case with Cursor AI
Session-7: Building MCP Servers from Scratch using LangChain, Building AI Agents with MCP Servers using LangChain and Groq
Session-8: Introduction to n8n as an Agentic AI workflow automation platform, Use cases with n8n from Web scraping to voice AI Agent
Unlock the Power of AI & GenAI with Dr.Anand
Course Instructor
Dr. S. Mahesh Anand is a distinguished educator, corporate trainer, keynote speaker, and consultant in the fields of Data Science, Machine Learning, and Artificial Intelligence. With over two decades of experience, Dr. Anand has been instrumental in shaping the learning journey of more than 50,000 students and professionals across India.
Dr. Anand served as a full-time faculty member at VIT University (Vellore) for a decade, where he honed his academic and research skills, before founding his consulting and training firm, Scientific Computing Solutions (SCS-India), in 2012.
His professional footprint includes delivering transformative corporate training sessions for leading organizations like Great Learning, Chegg, TNQTech, CGI, Mad Street Den and many startups, alongside conducting over 800 master training sessions for faculty members in higher education academic institutions across India.
Among his accolades, Dr. Anand is the recipient of the AT&T Labs Award from IEEE Headquarters and the M.V. Chauhan Award from IEEE India Council for his pioneering work in ANN-Fuzzy hybrid AI model for cancer prediction. He has also been recognized with the Best Data Science & AI Educator Award by AI Global Media, UK in the year 2022.
As the founder of "Learn AI with Anand" a flagship program of SCS-India, he continues to inspire learners through his cohort online courses.
MTM for GenAI LLMs: MTM-LLM
Session-1: Introduction to Byte Pair Encoding (Tokenization), Word Embeddings, Positional Encoding 
Session-2: Visualization and Interpretation of Word Embeddings & Positional Encoding
Session-3: Introduction to the Self Attention Mechanism in Encoder: Attention Score Vs Attention Vector, Multi-Head Attention, Latent Attention
Session-4: Role of Feed Forward Layers, Mixture of Experts (MoE) & different output layer configuration for encoder only BERT/RoBERTa
Session-5: Loading and Inferring BERT, Transfer Learning, BERT as feature extractor, Full Model Training for BERT
Session-6: Introduction to Decoder Side of Transformer, Masked Self Attention and Cross Multi-Head Attention.
Session-7: End-to-End Encoder-Decoder Transformer for GenAI Tasks, Loading GenAI models like GPT Series/Gemini, Llama, Gemma for direct Inference
Session-8: Introduction to RAG, Docstore and VectorDB, Llama Index and LangChain Frameworks
Session-9: Advanced RAG Systems: MergerRetriever, MultiVectorRetriever, Cross Encoder based Re-Ranking
Session-10: Advanced Fine-Tuning Techniques for LLMs: Exploring LoRA, PEFT, and QLORA Techniques for Llama & Gemma Models
Session-11: Multi-AI Agent Systems, Crew & Google Gemini, LLM evaluation metrics: Faithfullness & Context Relevance using RAGAS
Session-12: Deploying LLMs as APIs: Integration with LangChain and FastAPI, Standalone Vs Cloud Base Configurations
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