About Introduction to Artificial Intelligence and Data Science (GNEST305)
Introduction to Artificial Intelligence and Data Science (GNEST305) is a third-semester course in the KTU B.Tech 2024 scheme, common to non-computer branches such as ECE, EEE, Civil and Mechanical Engineering. It introduces the core ideas behind AI, machine learning and data science, and the maths that makes them work, so engineers in every field can use data to solve problems.
Syllabus
- Module 1: Introduction to AI and machine learning: types of ML systems and their challenges, regression, logistic regression for classification, and K-means clustering.
- Module 2: Mathematical foundations: the linear algebra used in AI and data science, including matrix decompositions such as singular value decomposition (SVD).
- Module 3: Applied probability and statistics for AI and data science.
- Module 4: Basics of data science: the data science process, big data, and how data is collected, prepared and analysed.
Exam pattern
The end-semester exam is for 60 marks: 8 short questions of 3 marks each, plus 4 questions of 9 marks each, one from each module. Internal assessment adds 40 marks.
Study tips
Learn the key definitions and compare related ideas clearly, such as supervised vs unsupervised learning and classification vs regression. Practise the numerical problems in linear algebra and statistics step by step, and solve previous question papers to see which topics repeat.
Notes and resources
Find module-wise notes, solved problems, previous year question papers and the syllabus for GNEST305 here, shared by KTU students and teachers.