Learn to build SLMs, from scratch
Duration : 1 year Classes : 72 Days : Weekdays / Weekends
Meet the Small Language Model (SLM) - a compact powerhouse designed for speed, efficiency, and precision. SLM delivers the core capabilities of generative AI without the heavy compute costs, making it ideal for edge devices, real-time applications, and privacy-sensitive environments. Whether you're building chatbots, summarizing content, or automating tasks, SLM offers lightning-fast performance and customizable intelligence that fits seamlessly into your workflow. It's AI that's lean, agile, and ready to deploy-because big ideas don't always need big models.
Deploy the power of AI at the edge or on-premises to ensure data privacy and achieve ultra-low latency. Choose the SLM for lightweight, budget-friendly deployment that provides a laser focus on your specific business challenges, without the computational burden of larger models.
SLMs represent a major advancement in NLP, transforming how machines process and understand language. SLMs ability to perform a broad range of tasks with minimal task-specific training makes them highly versatile. The course is structured to guide learners from foundational knowledge about natural language processing (NLP) to advanced concepts such as pre-training, fine-tuning, and deploying SLMs.
Our SLM course is the ultimate gateway to leveraging the capabilities of NLP & AI to revolutionize how we interact with languages. Students will gain profound insights into SLM components, mastering algorithms that enable machines to create content, simulate human behavior, and generate descriptive solutions.
This course is intended to prepare you for performing cutting-edge research in natural language processing, especially topics related to pre-trained language models. During this training, you shall be able to build, train and deploy Small Language Models at scale.
Target Audience:-
- Engineers and Managers
- Under-Graduate Engineers
- Post-Graduate Engineers
- Govt officers and Executives working on SLM/LLM projects
- Domain experts who want to develop an overall understanding of SLM/LLMs
- Anyone who wants to understand the fundamentals of SLM/LLMs
- Students who want to add SLM/LLM Engineer / SLM/LLM Scientist capabilities to their curricular
Course Format:-
✔ The course shall be delivered through a combination of lectures, interactive discussions & case studies
✔ Participants are exposed to practical exercises and new-age projects, where they learn by doing
✔ Participants shall have access to online resources, including reading materials, videos & business simulations
✔ Students shall receive all the study material
✔ Guest speakers from the industry may be invited to share insights and experiences
✔ Regular assessments and quizzes will be conducted to reinforce learning
✔ This is a Classroom only training
✔ Corporates: We understand your specific needs and goals. Contact us for customizations to this training
Trainers:-
✔ Equipped with multidisciplinary backgrounds
✔ Experts from the field of Maths, Financial Markets, AIML, Data Science & Management
✔ Each with over 25+ years of International experience working in EU / US / Australia
✔ All our trainers are Highly Qualified and Certified, in their respective subject areas
This syllabus provides a structured, module-by-module breakdown of this comprehensive training program focused on participants overall performance, retention, and engagement, covering foundational theory, implementation, best industry practices and advanced techniques in the subject.
Module 1: Recap and Intro to SLMs
✔ Advanced Python Recap
✔ ML Recap
✔ DL Recap
✔ NLP Recap
✔ OpenAI API
Module 2: SLM Fundamentals and Architecture
✔ The SLM Value Proposition
✔ SLM Architectures
✔ Data Curation for Specialization
✔ Evaluation Metrics for SLMs
✔ Key design trade-offs: size vs. performance
Module 3: Parameter-Efficient Fine-Tuning (PEFT)
✔ Introduction to PEFT
✔ Instruction Tuning (SFT)
✔ Data Formatting and Training
✔ Alignment and RLHF/DPO
✔ Transformer basics and lightweight variants
✔ Parameter reduction techniques
Module 4: Training & Fine-Tuning
✔ Dataset selection and preprocessing
✔ Transfer learning and domain adaptation
✔ Low-resource training techniques
✔ Evaluation metrics for SLMs
Module 5: Model Compression and Quantization
✔ Quantization Techniques
✔ Pruning and Sparsity
✔ Knowledge Distillation
✔ Inference Optimization
Module 6: Edge and Private Deployment
✔ On-device deployment (mobile, IoT, embedded systems)
✔ On-Premise Deployment (GGUF)
✔ Containerization and Serving
✔ Integration with RAG Pipelines
✔ Energy-efficient inference strategies
Module 7: Privacy, Safety & Ethics
✔ Federated learning and differential privacy
✔ Bias mitigation in small models
✔ Safety constraints and ethical considerations
✔ Regulatory compliance (GDPR, HIPAA)
Module 8: Capstone Project
✔ Design, train, and deploy a custom SLM
✔ Present architecture, performance benchmarks, and use case
✔ Peer review and feedback
Student Reviews
Bhawana
Fabulous NLP + ML course
I have eleven plus years of experience taking training courses. I do not usually complete surveys.
Your instructor was excellent, the best I've experienced on a software subject, and I couldn't imagine him doing a better job of seamlessly walking students through a breadth of information for such complex subject like AI and ML. he did a fabulous job pacing everything and addressing student questions. I am very impressed.
Harish
Excellent ML course!
The course was well structured and easy to understand. Good pace of learning.
The institute believes to provide knowledge as well as guidance in detail to each & every student.
I completed my ML course from the institute. Their international exp does help a lot !
Thanks for the training sir.