in collaboration with
Branch - Applicable across all engineering branches
Machine Learning is an application of Artificial Intelligence (AI) that provides systems the ability to automatically learn and improve from experience without being explicitly programmed. Machine Learning focusses on the development of computer programs that can access data and learn from it.
The Machine Learning market size is expected to grow from $1.03 billion in 2016 to $8.81 billion worldwide by 2022, at a Compound Annual Growth Rate (CAGR) of 44.1% during the forecast period owing to a large number of new job openings.
Machine Learning for Real-World Application is a course that teaches the basic and advanced concepts of Machine Learning supported by industry relevant business case studies. The course uses Python as the programming environment. Datasets required for the case studies can be obtained from the internet. This state-of-the-art course is available for engineering students who aspire to take part in knowledge building and make computers capable of taking intelligent decisions in several areas such as smart home applications, providing bank loans to customers, business analytics including share market predictions, sentiment analysis, security and surveillance, real estate businesses and more.
A virtual hands-on environment is integrated within the course.
Students will have to leverage this environment to complete the industry assignment as well as to complete the Part B section of the summative assessment.+ Read More - Read Less
- Linear Algebra: Matrices and Vectors
- Calculus: Differentiation, Partial Derivatives and Gradient
- Statistics: Descriptive Statistics, Normal Distribution, Probability
- Basic Programming
- Data Processing using NumPy, SciPy, Matplotlib and Pandas
- Basic usage of Scikit, Scikit-learn packages in Python