Artifical Intelligence & Machine Learning Starts 29 Apr, 2022

This course will help students gain expertise in various machine learning algorithms such as regression, clustering, decision trees, random forest, Naïve Bayes, and Q-Learning. It will also help students understand the concepts of Statistics, Time Series, and different classes of machine learning algorithms like supervised, unsupervised, and reinforcement algorithms.

Artifical Intelligence & Machine Learning
Curriculum
The course will be scheduled in three parts as follows:
1. Data Science Fundamentals
Topics Covered: Python Scripting, Object-Oriented Programming, Introduction to Data Science, Data Extraction, Wrangling, & Visualization
2. Machine Learning with Python
Topics Covered: Machine Learning with Python Fundamentals, Supervised Learning, Dimensionality Reduction, Unsupervised Learning 3. Advanced Machine Learning
Topics Covered: Association Rules Mining and Recommendation Systems, Reinforcement Learning, Time Series Analysis, Model Selection, and Boosting

Course Details
1. Students will understand the roles played by a Machine Learning Engineer.
2. Students will automate data analysis using python
3. Students will analyze use cases in real-world scenarios on machine learning applications.
4. Students will learn tools and techniques for predictive modeling.
5. Students will practice implementing types of classification methods, including SVM, Naive Bayes, decision tree, and random forest.
6. Students will interpret unsupervised learning and apply clustering algorithms.
7. Students will understand Time Series and its related concepts.
8. Students will import and wrangle data using Python libraries and divide them into training and test datasets.
9. Students will build real-world solutions using Machine Learning algorithms.

Projects
There will be one final project for this course. The problem statement will be given in context of a real-world data set and will be uploaded on the LMS. The date of final project submission and project presentation will be given in class and posted on the LMS.

FAQs
How do I interact with the educator during the class?
You can interact with the educator during the class using the chat feature.

What if I have queries related to the topic after the class?
We provide 24*7 live support to all our students via live chat feature and email. Our academic enablers are always available to help you throughout the course.

How will I be graded?
You will be graded on the basis of weekly quizzes, assignments, lab engagements, midterm and final exams.

Is the course material accessible to the students even after the course is over?
Yes, the course material is accessible to the students even after the course is over in the form or PDF documents and recorded lectures.