- Prof. Carl Gustaf Jansson via NPTEL
- Co-ordinated by: IIT Madras
- 8 Weeks duration
- Discipline: Computer Science and Engineering
- Language: English
What is this Course about?
This is a brilliant course for anyone who is looking forward to learning the details regarding Machine Learning. This course will give you an insight into computer algorithms. You will look at how the computer algorithms improve automatically through experience and by the use of data.
What will you learn through this Course?
This an eight-week-long course, and through this course, you will be learning:
In the first week, you will start by getting a brief introduction to Machine learning. Moving on, you will get into the details for, Foundation of Artificial Intelligence and Machine Learning. Additionally, the instructors will help you learn about Intelligent Autonomous Systems and Artificial Intelligence. By the end of this week, you will know all of the applications of Machine Learning.
This week will start by getting you familiar with the characterization of Learning Problems. You will study the feature-related issues. Moreover, you will look into the scenarios for Concept Learning.
Moving on, you will study in detail the form of representation, decision trees, and belief networks. All of the previously gained concepts will help you to get familiar with Artificial Neural Networks. By the end of this week, you will know everything about generic algorithms and logic programming.
This week is all about learning the Symbolic Representations and Weak Theories. You will get to investigate the topics of Generalization as Search, Decision Tree Learning Algorithms, Instance-Based Learning, and Cluster Analysis.
Week 5 may seem like a roller coaster of concepts. In this week, you will start by learning about Inductive Logic programming and Reinforcement Learning. You will end the week by studying the case- Based Reasoning.
Week 6 is filled with a lot of information and knowledge. So, you might not want to skip this week. You get to study the artificial Neural Networks, Perceptron’s, Model of neurons in an ANN. Moreover, you will get to know about the Recurrent Neural Networks, Hebbian Learning, and Associative Memory, etc.
In the second last week, you will get to understand the tools and resources that can be used. You will study everything about tools and their applications. After learning about the tools, you will move forward on learning about Interdisciplinary inspiration.
In the last week of this course, you will get fully prepared for the exam. Moreover, you will look into the applications, their example, and their uses.
More Related Courses:
- DeepLearning.ai via Coursera
- 5 hours of effort required
- 308,994+ already enrolled!
- ★★★★★ (44,735 Ratings)
- Stanford University via Coursera
- 64 hours of effort required
- 3,768,682+ students enrolled
- ★★★★★ (151,613 Ratings)
There are no reviews yet. Be the first one to write one.