This programme is a mix of data analytics and optimization tools, and primarily covers the recent developments in the area of machine learning. It will have a strong focus on applications and working of the algorithms so that the participants get a thorough insight in the field of data science. The programme takes a practice-based approach for teaching concepts and tools that are needed for making data driven decisions in business. The participants in this course are expected to have a strong quantitative background to be able to finish the course successfully.
The objective of the course is to introduce various methods from the domains of machine learning and optimization that will be useful to make business decisions when faced with large amount of data. The objectives of the course are as follows:
Following are the concepts that will be covered during the programme.
A three-hour Python video tutorial customized for the participants will be shared before the start of the programme.
Following are the products that the participants will be trained on building during this programme:
The code/models/datasets for all the above products will be shared with the participants during the programme.
INR 98,000 plus GST per person for participants from India and its equivalent in US Dollars for participants from other countries.
The programme will be targeted towards participants and organizations that are looking to build expertise in data science and intend to utilize machine learning tools for their data analysis needs. The cohort will be a mix of junior and middle level participants with at least a bachelor’s degree. The bachelors or higher degree should have provided sufficient exposure to the participants on mathematics and computing.
Follow the following link for online registration: https://web.iima.ac.in/exed/programme-details.php?id=ODA5
For any query on programme content, please contact: Prof. Ankur Sinha (email@example.com)
For any administrative support, please contact: Ashutosh Rajput (firstname.lastname@example.org)