About the Course
MIT offers a cutting-edge online course called the No-Code Artificial Intelligence (AI) and Machine Learning (ML) Programme that is aimed at helping professionals use AI and ML without having to be coding experts. This course, offered by MIT Professional Education, gives students a thorough understanding of AI and ML ideas, tools, and applications so they may apply these technologies across a range of sectors. Participants will acquire practical experience using no-code AI and ML platforms, investigating real-world case studies, and creating AI-powered solutions. This course places a strong emphasis on practical learning. Data analysis, predictive modelling, natural language processing, and computer vision are among the topics covered in the course syllabus. Participants will leave the programme with the abilities and knowledge needed to put AI and ML solutions into practise, enabling them to promote innovation and improve decision-making in their particular industries.
Potential Recruitment Companies
Amazon, TCS, Adidas, FICO, Accenture
Admissions Criteria
For Indian Participants: Graduates or Diploma Holders from a recognized university in the any field are eligible to participate. For International Participants: Graduation or an equivalent degree from a recognized University or Institution in any field in their respective country is required.
Potential Job Profiles
Data Scientist, Machine Learning Engineer, Data Analyst, Business Analyst
Career Progression
With experience, Data Scientists can move into senior roles such as Lead Data Scientist, Principal Data Scientist, or Chief Data Scientist. They can also move into other related roles such as Machine Learning Engineer, Data Architect, or Data Engineer.
Perks Of Industry
The data science industry is growing rapidly, and there is a high demand for skilled Data Scientists. Data Scientists can earn high salaries and have the opportunity to work on cutting-edge technologies.
Eligibility For Joining The Course
Bachelor Degree or Master Degree with a minimum of 50% marks and the knowledge of fundamentals of mathematics and statistics.
