Course Content Get the detailed Course Information here. - Chapter 1: Introduction
- Chapter 2: Solving Business Problems Using AI and ML
- Chapter 3: Collecting and Refining the Dataset
- Chapter 4: Setting Up and Training a Model
- Chapter 5: Finalizing a Model
- Chapter 6: Building Linear Regression Models
- Chapter 7: Building Classification Models
- Chapter 8: Building Clustering Models
- Chapter 9: Building Decision Trees and Random Forests
- Chapter 10: Building Support-Vector Machines
- Chapter 11: Building Artificial Neural Networks
- Chapter 12: Promoting Data Privacy and Ethical Practices
| Hands on Activities (Live Labs) - Collecting and Refining the Dataset
- Setting Up and Training a Model
- Building Linear Regression Models
- Building Classification Models
- Building Clustering Models
- Building Decision Trees and Random Forests
- Building Support-Vector Machines
- Building Artificial Neural Networks
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This course can be customized to fit the specific needs of the attendees and the company or industry they operate in.
Get the detailed Course Datasheet here.
Below are some of the career paths and potential opportunities after passing the Certified Artificial Intelligence Practitioner exam.
- AI Developer
- Data Scientist
- Avatar Animator
- Applied Scientist
- Research Scientist
- Machine Learning Scientist
- Conversation/Content interface writer
There are no pre-requisites for taking this course. A passion for Artificial intelligence will go a long way.