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AKTU Introduction to AI & Machine Learning (MNDS501) Syllabus PDF – B.Tech Minor Degree in Data Science
Introduction to AI & Machine Learning MNDS501
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- Semester 5
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Official AKTU syllabus of Introduction to AI & Machine Learning (MNDS501) for B.Tech Minor Degree in Data Science – 4 credits, L-T-P 3-1-0. Read the unit-wise course content, course outcomes, evaluation pattern and recommended books online, or download the PDF.
Syllabus — Introduction to AI & Machine Learning
Download PDFMNDS501 · 4 credits · L-T-P 3-1-0
Course Outcomes
At the end of course , the student will be able to understand
| CO 1 | Provide you with the knowledge and expertise to become a proficient data scientist. |
| CO 2 | Demonstrate an understanding of statistics and machine learning concepts that are vital for data science |
| CO 3 | The student will learn to apply knowledge representation techniques and problem solving strategies to common AI applications. |
| CO 4 | Critically evaluate data visualisations based on their design and use for communicating stories from data; |
Course Content
| Unit | Topic | Proposed Lecture |
|---|---|---|
| I | Linear Regression: Basic facts of linear regression, implementation of linear regression, case studies of linear regression using data set. | 08 |
| II | Logistic Regression: Basic facts and implementation of logistic regression, solve a case study to predict output using existing data set | 08 |
| III | Clustering and Principle Component Analysis: K means and hierarchical clustering, how to make market strategies using clustering, recommendation and PCA | 08 |
| IV | Support Vector Machine: basics of SVM and use it to detect the spam emails and recognize alphabets | 08 |
| V | Model Selection and advanced regression: use of Lasso and Ridge | 08 |
Text Books
- Machine Learning using Python , U Dinesh Kumar and Manaranjan Pradhan,John Wiley & Sons.
- Advanced Data Analytics Using Python: With Machine Learning, Deep Learning by By Sayan Mukhopadhyay, Apress.
- Practical Data Mining” by Monte F. Hancock, Auerbach Publication.
- “Machine Learning for Absolute Beginners: A Plain English Introduction (SecondEdition)” by Oliver Theobald.
- Practical Data Science with R, Nina Zumel, John Wiley & Sons.
- Python for Data Science for Dummies, John Paul Mueller, Luca Massaron, John Wiley & Sons.
- Big Data and Analytics, Seema Acharya and Subhashini Chellappan, Wiley Publication.
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