Collegesangi

Menu Hover Effect on Active Page – Unique 12 Version
Site Logo
AI Powered
Diploma in Data Science / AI
Apply Now πŸ”₯ Trending
Course Mode
Offline
Duration
1-2
Eligibility
Passed 10+2 from a recognized board. , While not always mandatory, having a background in the science stream with Mathematics and a basic understanding of computers is highly recommended and often a prerequisite for some institutes.
Entrance Exam
Generally, there are no specific entrance exams for diploma programs. Admissions are typically based on merit from the last qualifying examination (10+2). Some institutes may conduct a basic aptitude test or a personal interview.
Type of Course
Diploma
Share this Course

Course Summary

A Diploma in Data Science / AI is a vocational program that provides students with the foundational skills needed to enter the rapidly growing fields of data science and artificial intelligence. The curriculum focuses on practical, hands-on training in key areas such as Python and R programming, statistics, machine learning algorithms, and data visualization. Students learn to collect, clean, analyze, and interpret large datasets to extract meaningful insights and build intelligent systems. This course is ideal for those who have a strong aptitude for mathematics, problem-solving, and a keen interest in technology, but may not be seeking a long-term undergraduate degree. It serves as a fast-track entry point into the tech industry or as a stepping stone to further education.

πŸ“… Upcoming Admission Deadlines

  • diploma-in-data-science-ai with 50% scholarship August 28, 2025

Top Recruiters

TCS
Wipro
Infosys
Capgemini
Accenture
IBM
Cognizant
Amazon
HCL Technologies

Career Scope

βœ”
Β Network Engineer
βœ”
Frontend Engineer
βœ”
Electric Engineer
βœ”
Software Developer
βœ”
Web Developer

College-wise Fees

Frequently Asked Questions

AI: is the broad concept of creating systems that mimic human intelligence. Machine Learning (ML): is a subset of AI that focuses on algorithms learning from data to make predictions or decisions without explicit programming. Data Science: uses scientific methods, processes, algorithms, and systems to extract knowledge and insights from structured and unstructured data, often applying ML to achieve its goals.
Technical Skills: Proficiency in programming languages (like Python), familiarity with ML frameworks (TensorFlow, PyTorch), database management, and data analysis tools are crucial.
Personalized Experiences: Recommender systems in e-commerce, personalized news feeds, and tailored product recommendations. Automation: Self-driving cars and drones performing tasks that require autonomous operation and real-time decision-making. Healthcare: AI-powered medical diagnostics, drug discovery, and personalized treatment plans are transforming the medical field.
πŸ“ž Need Help? Talk to a Course Advisor
Get Free Advice