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Modules Overview — ML & LLM Curricula

High-level summaries of Machine Learning, Large Language Models, and Advanced LLM course tracks.

Format: Lectures, Labs, Projects

Machine Learning Syllabus

A practical, end-to-end machine learning curriculum covering fundamentals to deployment. Students learn data preprocessing, feature engineering, supervised and unsupervised learning, deep learning for vision and NLP, and production workflows for model deployment and monitoring.

  • Foundations: Python setup, libraries, visualization, Gaussian distributions.
  • Data prep: Cleaning, scaling, encoding, PCA/LDA, train/test splits, cross-validation.
  • Modeling: Regression, classification, tree-based methods, SVM, ensemble learners.
  • Deep learning: MLPs, CNNs, RNNs, transformers; practical apps in vision and NLP.
  • Deployment & MLOps: Flask/FastAPI/Streamlit, cloud deployment, CI/CD, monitoring.

Large Language Models (LLM) Syllabus

An in-depth course on the mathematics and architectures behind modern LLMs, starting with core math and progressing through neural networks, transformers, and practical LLM techniques like fine-tuning, PEFT, and RAG.

  • Foundations: Linear algebra, probability, calculus, optimization, backpropagation.
  • Architectures: Evolution from RNNs to Transformers; attention mechanisms and positional encoding.
  • LLM workflows: Pretraining, fine-tuning, prompt engineering, PEFT (LoRA, Adapters), RAG.
  • Scaling & compute: Tokenization, model/data parallelism, infrastructure considerations.
  • Ethics & safety: Bias, fairness, and responsible model use.

Advanced LLMs Syllabus

A roadmap for mastering large-scale LLM systems: architectures, optimization, deployment, and evaluation of state-of-the-art models and multimodal systems.

  • Advanced topics: Multi-head attention, scaling laws, efficient architectures (sparsity, mixture of experts).
  • Modern models: GPT-family, T5, LLaMA, multimodal systems (GPT-4V, Flamingo).
  • Customization & tuning: PEFT, RLHF, Chain-of-Thought, prompt optimization strategies.
  • Production readiness: Quantization, pruning, self-hosting vs API, latency and cost optimizations.
  • Evaluation: BLEU/ROUGE/F1, hallucination detection, bias mitigation, benchmarking.

Why Learn With Us?

Industry-Driven Curriculum

Learn the latest AI techniques used by top companies.

Hands-On Projects

Apply your skills with real-world projects and case studies.

Expert Instructors

Learn from AI researchers and industry professionals.

Flexible Learning

Self-paced and live classes to fit your schedule.

Training Certificates

Boost your career with recognized AI & ML certifications.

Global Networking

Connect with professionals and build industry relationships.

World-Class Faculty You Can Trust

At Isanghan Minds, your learning is guided by experts who don’t just teach AI—they’ve built it.

Lead Instructor

Suresh

Lead Instructor (PhD)

PhD holder with 15+ years of real industry experience designing real-world ML and AI solutions. A graduate from internationally renowned universities, bringing cutting-edge academic depth to practical applications.

15+ Years Experience
Senior Mentor

Praveen

Master’s Expert

Industry-seasoned Master’s professional with over 10 years of hands-on expertise. Has applied AI in companies worldwide, ensuring you receive internationally aligned training that is real-world ready.

10+ Years Experience

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About
Isanghan
Minds

Isanghan Minds is an education technology company that specialises in online teaching of cutting edge courses on Machine Leaning, and Artificial Intelligence etc.,

Our courses are designed for beginners, professionals, and AI enthusiasts looking to build expertise in the most in-demand technologies. For more details refer thr course page.

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