Machine Learning is a 4 year course which works in a similar way to human learning. Students have now become more vigilant regarding the course that they want to pursue in future. Machine learning works in a specific way: data input is done with certain commands so that the computer is enable to learn to identify certain objects and distinguish between them.
Students now a days are very smart and they tend to make informed decision. They collect information regarding syllabus and other important topics. For your convenience the syllabus for each semesters is written below.
Semester 1
• Introduction to machine learning
• Programming for problem solving
• Maths 1
• Engineering physics
• Computer aided design and drafting
• Principles of electrical and electronics engineering
• Soft skills 1
Semester 2
• Application based programming in algorithm
• Maths 2
• Advanced physics
• Engineering chemistry
• Mechanical workshop
• Soft skill 2
• Multimedia application lab
• Project based learning 1
Semester 3
• Building essential language and life skill
• Introduction to biology for engineers
• Discrete structures
• Computer organisation and architecture
• Data Structure using C plus
• Project based learning 2
Semester 4
• Principles of operating system
• Computer networks
• Database management system
• Management course
• Project based learning 3
• Environmental science
• Advanced Java lab
Semester 5
• Design and analysis of algorithm
• Theory of computation
• Software engineering and testing methodologies
• Elective program 1
• Project based learning 4
Semester 6
• Compiler design
• Artificial intelligence
• Technical skill enhancement course
• Project based learning 5
Semester 7
• Web technologies
• Major project 1
• Comprehensive examination
• Professional ethics and values
• Industrial internship
• Introduction to Deep learning
Semester 8
• Major project 2
• Universal human values and ethics
• Robotics and intelligent system
