Smart Professional-Artificial Intelligence and Machine Learning (OV-7142)
Course Overview
| Module | Duration (Instruction al Hours) | Theory | Lab | Self-Study | Tool/Software |
|---|---|---|---|---|---|
| Managing Large DataSets with MongoDB | 32.00 | 16.00 | 16.00 | 12.00 | MongoDB 6.x |
| Application Based Programming in Python | 36.00 | 18.00 | 18.00 | 10.00 | Python NLP Tools and Libraries JupyterNotebook, Google Collab TensorFlow |
| Data Science using R Programming | 36.00 | 18.00 | 18.00 | 8.00 | " |
| AI Primer | 16.00 | 16.00 | 0.00 | 16.00 | " |
| AI Applications of NLP | 40.00 | 20.00 | 20.00 | 8.00 | " |
| AI and ML with Python | 40.00 | 20.00 | 20.00 | 12.00 | " |
| Applied Machine Learning using Python | 40.00 | 20.00 | 20.00 | 12.00 | " |
| Deep Learning using Neural Networks | 60.00 | 30.00 | 30.00 | 12.00 | " |
| Capstone Project-Recommendation Engine and Customer Churn Prediction | 40.00 | 2.00 | 38.00 | 0.00 | " |
| Total Hours | 340.00 | 160.00 | 180.00 | 90.00 |
EXIT PROFILE
AI Developer
CERTIFICATE NAME
Smart Professional- Artificial Intelligence and Machine Learning
LEARNING OUTCOMES
- Understand the basics of statistical analysis, descriptive statistics, predictive analytics, probability, and Bayes theorem
- Gain an understanding of AI
- Gain knowledge in NLP and learn the use of AI in NLP
- Use important building blocks of AI ML with Python, make data modelling decisions, interpret output of the algorithms, and validate results
- Master ML concepts and techniques including supervised and unsupervised learning, mathematical and heuristic aspects, and hands on modeling to develop AI algorithms
- Master deep learning concepts and TensorFlow open source framework, implement deep learning algorithms, and build ANN
- Develop a real world Capstone project on recommendation engine and perform customer churn prediction