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What should I do after 12 from PCM and computer science C++?


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7 answers

RE: What should I do after 12 from PCM and computer science C++?

Ankeeta hatwar
Ankeeta hatwar

B.Sc. Nautical Science.

B.E. Marine Engineering.

B. Tech (Bachelor of Technology)

BCA (Bachelor of Computer application)

BS (Bachelor of Science in computer engineering)

B.E. Civil Engineering.

B.E. Electrical & Electronics Engineering.

B.Sc in aviation.

Also check out for more info: https://marketresearchcommunity.com/

RE: What should I do after 12 from PCM and computer science C++?

Ankeeta hatwar
Ankeeta hatwar

B.Sc. Nautical Science.

B.E. Marine Engineering.

B. Tech (Bachelor of Technology)

BCA (Bachelor of Computer application)

BS (Bachelor of Science in computer engineering)

B.E. Civil Engineering.

B.E. Electrical & Electronics Engineering.

B.Sc in aviation.

Also check out for more info: https://marketresearchcommunity.com/

 

https://marketresearchcommunity.com/

RE: What should I do after 12 from PCM and computer science C++?

soniyasinghania
soniyasinghania

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RE: What should I do after 12 from PCM and computer science C++?

siksha education
siksha education

Considering your background in PCM (Physics, Chemistry, Mathematics) and Computer Science with C++ programming, you're well-equipped for a career in data science. Here's a suggested path:

  1. Understand the Basics: Ensure you have a strong foundation in mathematics, particularly statistics and linear algebra. Familiarize yourself with programming languages commonly used in data science such as Python and R.

  2. Enroll in a Data Science Course: Look for reputable online platforms like Coursera, edX, or Udacity that offer data science courses. Choose a course that covers topics like data analysis, machine learning, data visualization, and big data.

  3. Specialize in Data Science: Some courses offer specializations within data science, such as natural language processing, computer vision, or deep learning. Choose a specialization based on your interests and career goals.

  4. Hands-on Experience: Theory is important, but practical experience is invaluable. Work on projects that involve real-world data analysis, preferably using datasets related to your interests. Kaggle is a great platform for finding datasets and participating in data science competitions.

  5. Internships and Networking: Seek internships or volunteer opportunities in data-related roles to gain practical experience and build your network in the industry.

  6. Continuous Learning: Data science is a rapidly evolving field, so stay updated with the latest trends, techniques, and tools by reading blogs, attending workshops, and participating in online communities like Stack Overflow and GitHub.

By following these steps, you'll be well on your way to becoming a proficient data scientist.

Take The Ideal Career test Here

Ideal Career Test Inlcudes:

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Caching Date: 3/27/2026 8:40:11 PM