Both artificial Intelligence and Data Science are booming career paths among students who want to work in technology. But post Class 12 most students are confused as to which course is more suitable to their goals. There are many entry points into AI and Data Science programs and students can opt for various degree programs given how much they want to go for software development, analytics, mathematics, or machine learning.
1. B.Tech in AI and Data Science
A B.Tech in AI and Data Science is an easy take for students who want an engineering based course. Typically, the course fields the subjects programming math statistics, data base, data structures, machine learning and artificial intelligence.
Beyond the theoretical courses, students can design projects, which help to learn how AI and data are used for practical domains.
2. B.Tech CSE with AI, ML, or Data Science.
If students do not want to be confined to a specific technology then they can pursue Computer Science Engineering (3 Year/ 4 year), with a specialization in AI / Machine Learning/ Data Science.
The benefit of taking this route, that students would gain a wider knowledge in Computer Science, and would also be able to gain some experience with more recent topics such as machine learning and AI.
3. BCA with AI or Data Science
Can be a good avenue after Class After Class 12, if you want to excel in programming, software usage, but don't want to do engineering.
Typically specialised BCA courses offered at some universities will include courses in AI, Machine Learning, Data Analytics and other futuristic courses.
4. B.Sc. In Statistics and Data Science
Students who love mathematics and conducting statistical analysis are interested in this such B.Sc. Programme. This Data Science and Statistics.
The second path emphasises on having knowledge and skills in data, statistical techniques programming analytical techniques, which are helpful to pursue career in analytics and data banks.
What skills are valuable in AI and Data Science?
Whatever degree a person takes, course title on its own, will not suffice. Hands-on skills are just as important. People should slowly acquire the basics of Python, SQL and data structures.
Familiarity with statistics, data visualisation, machine learning, and problem solving can be helpful as well. Getting involved in personal projects and internships can be a great way to stay sharp while applying academic skills to real-life scenarios.
Career Options After These Courses
Once general education requirements are completed and the necessary skills have been acquired, students are able to look into many potential career options, including:
Data Analyst
Data Scientist
AI Engineer
Machine Learning Engineer
Data Engineer
Business Intelligence Analyst
The career guidance of the student would be based upon the skill set projects internships and other learning with the degree title considering as just an identifier.
Which ones should we use?
Don't decide to go for a course based on whether AI or Data science is 'hot' in the market. Analyse the subjects offered, eligibility criteria, the extent of practitioner exposure, project work, internship opportunities, open positions, scope etc. across various other institutions.
For example, students exploring these fields can find options such as AI & Data Science, CSE specialisations, BCA and Statistics & Data Science at institutions such as SGT University.
Source: https://sgtuniversity.ac.in/life-at-sgt/blogs/ai-data-science-courses-after-12th-india