AI + LLM Coaching for Students and IT professionals (0 – 10 years of exp.)

Share it with your senior IT friends and colleagues
Reading Time: 2 minutes

The most up-to-date, practical, relevant, and short AI + LLM Course and Coaching

Online coaching on Artificial Intelligence, Generative AI, Large Language Models and AI Agents to build a career in the AI domain or implement AI in your business.

Who will benefit most from this course?

Engineering students and IT Professionals with experience (up to 10 years) like Developers, Tech Entrepreneurs, DevOps Professionals, Data Engineers, ML engineers etc who want to learn AI + LLM quickly and easily.

Course Curriculum

Course Overview – Labs and Practical Applications

You will get access to the following Hands-on labs and you will also make the following working AI/ ML/ LLM Applications and tools

Hands-On Labs

  1. Pandas Lab
  2. Machine Learning Lab
  3. Deep Learning Lab
  4. Computer Vision Lab
  5. NLP Lab
  6. Building LLM Applications Lab
  7. Promot Engineering for Developers Lab
  8. LangChain Lab
  9. Function calling Lab
  10. Monitoring Langchain application with Langsmith
  11. RAG Lab
  12. Fine Tuning using Gradient
  13. Multi AI Agent using open-sourced LLM
  14. Deploying LLM – Deep Infra
  15. Deploying LLM – Replicate
  16. Deploying LLM – Runpod
  17. LM Scorer (Evaluation of LLMs)
  18. Deploying on AWS Sagemaker
  19. Deploying Langchain application with LangServe
  20. Multi AI Agent Debate using AutoGen (Delhi vs Mumbai)
  21. Langgraph – Intro Lab
  22. DSPy framework demo
  23. Small Language Models Lab
  24. Quantize any LLM Lab

Practical AI Tools/ Applications that you will build

  1. ML Classification model
  2. Image Segmentation
  3. Text-to-Voice
  4. AI video Generation
  5. Image Generation using Open Source models on Huggingface
  6. Calling any OpenSource LLMs
  7. GPT4 – API calling
  8. LLM Chatbot
  9. Multi-lingual Text Summarization
  10. YouTube video Summarization Tool
  11. Monitoring LLM using LangSmith
  12. Chat with your Own PDF
  13. LLM Chatbot for your proprietary data using the Google Cloud Platform
  14. Fine-tune Gemma models in Keras using LoRA
  15. ChatGPT + Google Search
  16. LLM Medical Agent
  17. Gradio Application
  18. Streamlit Application using Gemini Pro
  19. Evaluation of LLMs using Giskard
  20. AI Voice Assistant App using Multimodal LLM “Llava” and Whisper
  21. Multi Agent System to Tailor Job Applications
  22. LangGraph -Multi AI Agent System for coding
  23. Build a Web Crawler using Crawl4ai
  24. RAG application using LlamaIndex

Course Duration

Total (Classroom coaching) – 36 hours

1-hour session per day

Weekend batch – 18 weeks

Weekday batch – 9-12 weeks

It’s a short program but a rigorous one

Apart from these coaching sessions, you must spend around 2-3 hours extra doing practical/hands-on exercises.

Do you provide OpenAI credits?

Yes, we are affiliated with Microsoft for Startup Founders Hub and we have received OpenAI’s credits. We pass these credits to our learners so they can do practical exercises.

Course Mode

Instructor-led Interactive Online Classes.

Pre-requisite

Python (the ability to read code in Python)

(Most of the code in the Lab and Practical applications are already written)

Who is the teacher?

Nikhilesh Tayal – https://www.aimletc.com/about-me-nikhilesh-tayal/

LinkedIn – https://www.linkedin.com/in/nikhileshtayal/

Price

Check here – https://www.aimletc.com/ai-ml-etc-course-offerings-pricing/

More FAQs

Check – https://www.aimletc.com/faqs-ai-courses-for-senior-it-professionals/

For any further questions, please drop an email at nt(at)aimletc.com

Featured Image Source

Share it with your senior IT friends and colleagues
Nikhilesh Tayal
Nikhilesh Tayal
Articles: 70