AI Hot & new
This syllabus covers foundational concepts in AI, along with practical skills in programming
and implementing AI algorithms. Each week includes both theoretical concepts and hands-on
exercises to reinforce learning. Adjustments
can be made based on the specific interests and needs of the students and the available
resources.
Requirements for this course
- Basic understanding and experience with coding in Python. Basic understanding and experience with coding in Python.
- Must have completed one other programming course in college.
- Must have basic knowledge of using Jupyter Notebook
- 1 month training is prerequisite for 2 months training
- 2 months training is prerequisite for 3 months training
1 month training
- Learning Python ML Libraries (Numpy and Pandas)
- Using Jypyter Notebooks for publically available Dataset
- Slice and Dice Data for Machine Learning
- Supervised and unsupervised learning basics
2 months training
- Learn open source models on Hugging Face
- Customize and use a model from Hugging Face
- Work with a Keggle data set for one supervised learning model
- Work with a Keggle data set for one unsupervised learning model
3 months training
- Large Learning Model concepts and basics
- LLM types and parameters
- Using LLM with customization
- Using LLM with vector data
- 1 month : Basic understanding of AI and ML
- 2 month : Hands on with developing and customizing ML models and using in real-time AI Applications
- 3 month : Model utilization in real world and tuning and improvements of the models to solve the problems