Do you want to know how to Become an AI and Machine Learning Specialist with ease? If yes, then you are at the right place. Several institutes offer a training program for AI and ML; however, you need a reliable one to pursue a career.

In the end, we will introduce you to a reputed training institute offering a dedicated training program related to AI and ML skills. What are we waiting for? Let’s get started!

What Are AI and Machine Learning?

The vast topic of developing computer systems that can replicate human cognitive abilities, such as reasoning, problem-solving, and decision-making, to carry out challenging tasks is known as artificial intelligence (AI).

A branch of artificial intelligence called machine learning (ML) focuses on developing algorithms that let computers learn from data and gradually improve their performance without needing to be explicitly programmed for every situation.

Let’s take a look at how to Become an AI and Machine Learning Specialist by contacting a reliable training institute!

Key Skills Required to Pursue a Career in AI and ML

The following skills are required to pursue a career in AI and ML:

Programming Proficiency: Although C++ is necessary for high-performance, real-time AI like robots, mastery of Python is unavoidable due to its dominant ecosystem (TensorFlow, PyTorch, scikit-learn).
Mathematical Foundations: The foundation of all algorithms is a solid understanding of Calculus (for model optimization), Statistics/Probability (for data-driven prediction), and Linear Algebra (for data representation).
Data Engineering & Management: Data quality impacts model success; therefore, being able to use Big Data tools like SQL, Spark, or Hadoop and execute Data Wrangling (cleaning and processing raw data) is essential.
Specialized AI Frameworks: Practical experience deploying and monitoring models in production using MLOps technologies and Deep Learning architectures (such as Transformers for GenAI or CNNs for Computer Vision).
Soft Skills & Domain Knowledge: To negotiate the ethical implications of AI and convert complicated technological insights into economic value, one must possess strong problem-solving and communication abilities.

Why Choose AI and Machine Learning After 12th?

S.No.	Factors	Why?
1.	Future-Proof Career Stability	By 2030, AI and ML abilities are expected to generate 170 million new jobs as old professions are automated, making your expertise the foundation of the workforce of the future.
2.	Significantly Higher Earning Potential	In 2026, entry-level AI positions will pay 30–50% more than traditional software engineering, with fresher packages typically beginning between ₹6 and ₹12 LPA in India.
3.	Cross-Industry Versatility	These abilities enable you to operate in any field you are enthusiastic about, such as healthcare disease diagnosis, fintech fraud detection, or climate-tech solution optimization.
4.	Massive Talent Gap Advantage	Starting early gives you a big competitive advantage to fill high-ranking roles more quickly because the demand for AI talent is three times greater than the supply.
5.	Foundation for Global Innovation	After 12th grade, learning AI gives you the technical "superpowers" you need to create the next wave of revolutionary technologies, such as personalized learning platforms and driverless cars.

Top AI and ML Courses After 12th: Where to Start?

The following are the top AI and ML courses after 12th:

● B.Tech in AI & Data Science: A demanding four-year engineering degree with a strong technical foundation in sophisticated robotics, software, and hardware.

● IIT Madras BS in Data Science: A distinguished, adaptable, four-year online degree with no age restrictions and several entry/exit points (Diploma, BSc, and BS).

● BCA or B.Sc. in AI: For individuals seeking a quicker path to positions in software development and data analytics, this three-year, application-focused program is perfect.

● Professional Certification Tracks: Short-term, well-known programs from DeepLearning, Google, or IBM. AI that can develop employable talents in a matter of months.

● Specialized Online Degrees: 3-year online degrees with full accreditation that let you combine education with internships, such as those offered by Manipal or Amity.

Eligibility Criteria and Prerequisites for AI and ML Programs

S.No.	Factors	Why?
1.	Academic Stream	Although BCA and B.Sc. programs sometimes accept Commerce/Arts students with Mathematics or Computer Science, B.Tech/BE programs require a Science background with Physics, Chemistry, and Mathematics (PCM).
2.	Minimum Marks Requirement	While elite colleges like IITs and NITs usually set the threshold at 75% for general category applicants, most universities require an aggregate of 50% to 60% in Class 12.
3.	Entrance Exam Qualification	Premium B.Tech programs typically involve passing state/ university-specific exams like CUET, VITEEE, or KCET, or national exams like JEE Main and JEE Advanced.
4.	Foundational Math Proficiency	Since these are the fundamental languages needed to build and comprehend AI algorithms, you must have a solid understanding of linear algebra, calculus, and statistics.
5.	Language and Tech Literacy	The majority of international curricula require proficiency in English as well as fundamental computational thinking or logic-based problem-solving abilities.

How to Prepare for AI and ML Entrance Exams?

In the following ways, you can prepare for AI and ML Entrance Exams:

a) Master the "Big Three" of Math: Eighty percent of the mathematical underpinnings of AI algorithms are found in Linear Algebra (matrices), Calculus (gradients), and Probability.

b) Build Computational Logic: To hone the algorithmic thinking needed for the "Aptitude" and "Logic" portions, practice coding-decoding, syllogisms, and series completion.

c) Prioritize High-Weightage NCERT & PYQs: Solve Previous Year Questions (PYQs) from the previous five years to find recurrent patterns in Calculus and Algebra. Use NCERT as your foundation for fundamental ideas.

d) Simulate the Digital Environment: To develop the endurance and speed required for a three-hour digital exam, take weekly Computer-Based Tests (CBT) to make sure you are at ease using on-screen calculators and interfaces.

e) Leverage AI-Specific Sample Papers: To practice questions on data interpretation and fundamental ML theory, look for specialist mock exams for "Data Science & AI" (such as the GATE DA or IIT Madras Qualifier style problems).

Importance of Internships and Hands-on Projects in AI and ML

S.No.	Factors	Why?
1.	Bridging the "Theory-Gap"	Internships teach you 80% of ML job data cleaning that textbooks sometimes omit by forcing you to deal with "messy" real-world data that is biased or incomplete.
2.	Building a Verifiable Portfolio	Compared to a good GPA, a GitHub repository with unique, well-documented projects (such as a custom RAG-based chatbot) serves as a "technical resume" that employers value more highly.
3.	Understanding the MLOps Pipeline	Working with industry tools like Docker, Kubernetes, or AWS SageMaker to deploy, monitor, and scale models reminds you that AI is more than simply an algorithm.
4.	Developing Domain Expertise	Working on particular projects (such as AI in Fintech vs. Healthcare) enables you to get the "why" behind the data, enabling you to create models that address real-world business issues rather than only obtaining high accuracy scores.
5.	Networking and Mentorship	Internships put you in high-growth teams and give you direct access to experienced engineers who can provide career advice and "hidden" industry references that aren't advertised on job boards.

Salary Prospects for AI and ML Specialists in India

In 2026, entry-level salaries for AI and ML specialists in India will be between ₹6 and ₹12 LPA, while mid-level professionals with three to six years of experience would make between ₹15 and ₹30 LPA.

In major IT hubs like Bengaluru and Hyderabad, senior architects and specialists in Generative AI or MLOps frequently command packages surpassing ₹45 LPA to ₹1 Crore+.

Career Opportunities in AI and Machine Learning

S.No.	Job Profiles	What?
1.	Machine Learning Engineer	Focuses on creating and implementing scalable machine learning models that enable practical applications like fraud detection and recommendation engines.
2.	Data Scientist	Develops predictive models to direct high-level company strategy and examines enormous datasets to uncover hidden trends.
3.	AI Research Scientist	Works at the forefront of the discipline, creating novel neural network topologies and algorithms in labs or university environments.
4.	MLOps Engineer	Creates the pipelines necessary for AI models to operate dependably and automatically at scale, bridging the gap between development and operations.
5.	Generative AI Specialist	Focuses on diffusion models and large language models (LLMs) to create tools like creative media generators, code helpers, and custom chatbots.
6.	NLP Engineer	Focuses on "teaching" machines to comprehend, interpret, and produce human language (Natural Language Processing).
7.	Computer Vision Engineer	Creates systems that enable computers to "see" and process visual information, which is crucial for facial recognition and driverless cars.
8.	AI Product Manager	Serves as a liaison between technical teams and clients, establishing the goals and plans for products driven by artificial intelligence.
9.	Data Engineer	Creates the sturdy "plumbing" or infrastructure needed to gather, purify, and move the enormous volumes of data that AI systems require.
10.	AI Ethics Consultant	Helps businesses deal with the ethical and legal challenges of automation by ensuring that AI systems are impartial, transparent, and fair.

Conclusion: How to Stay Ahead in the Ever-Evolving AI and ML Field

Now that we have talked about how to Become an AI and Machine Learning Specialist, you might want to get reliable sources. For that, you can get in contact with Craw Security, offering the Six-Months Diploma in Artificial Intelligence (AI) and Machine Learning to IT Aspirants.

During the training sessions, students will be able to try their skills on various tasks under the supervision of AI and ML professionals. Moreover, online sessions will facilitate students in remote learning.

After the completion of the Six-Months Diploma in Artificial Intelligence (AI) and Machine Learning offered by Craw Security, students will receive a certificate validating their honed knowledge & skills during the sessions. What are you waiting for? Contact, Now!

Frequently Asked Questions

About Become an AI and Machine Learning Specialist

What is AI and Machine Learning, and why should I pursue it after 12th?

Pursuing AI and machine learning beyond the 12th grade offers a future-proof profession at the vanguard of global innovation with extraordinarily high earning potential. These fields are centered on developing intelligent systems that learn from data.

What are the essential skills required to become an AI and Machine Learning specialist?

The following skills are needed to become an AI and ML specialist:

a) Programming & Software Engineering,

b) Mathematical Foundations,

c) Data Engineering & Feature Management,

d) Advanced ML & Deep Learning Architectures, and

e) MLOps & Cloud Deployment.

What are the best courses available after 12th to learn AI and ML?

One of the best courses available for AI and ML skills is the Six-Months Diploma in Artificial Intelligence (AI) and Machine Learning offered by Craw Security.

Can I pursue AI and ML without a background in computer science?

If you enroll in specialized programs like the IIT Madras BS in Data Science or "Applied" AI courses, which are made especially to train non-CS students from the ground up, you can pursue AI and ML without having a foundation in computer science.

What are the eligibility criteria for AI and ML programs after 12th?

In order to be eligible for AI and ML programs in 2026, a 10+2 qualification with 50–60% marks is usually required. For engineering degrees (B.Tech), mathematics is required, while for application-based degrees (BCA/B.Sc) with a bridging course, it is frequently optional.

Are there any entrance exams for AI and ML courses after 12th?

Yes, there are a number of entrance exams for AI and ML courses in 2026. These include university-specific assessments like VITEEE, BITSAT, and the IIT Madras BS Qualifier, as well as national engineering exams like JEE Main and JEE Advanced.

What kind of internships can I do to gain practical experience in AI and ML?

Craw Security offers an internship after the completion of the Six-Months Diploma in Artificial Intelligence (AI) and Machine Learning.

What are the career opportunities for AI and ML specialists in India?

The following are the career opportunities for AI and ML specialists in India:

a) Machine Learning Engineer,

b) Data Scientist,

c) AI Research Scientist,

d) MLOps Engineer, and

e) Generative AI Specialist.

How much can I expect to earn as an AI and ML specialist?

In 2026, the beginning compensation for an AI and ML specialist in India is expected to be between ₹6 LPA and ₹12 LPA for new hires, between ₹15 LPA and ₹30 LPA for mid-level professionals (3–6 years), and between ₹45 LPA and ₹1 Crore+ for senior roles.

What are the future trends in AI and Machine Learning that I should be aware of?

You should be aware of the following future trends in AI and Machine Learning:

a) Agentic AI (From Assistance to Autonomy),

b) Multimodal AI Fusion,

c) Edge AI & "AI PCs",

d) Small Language Models (SLMs) & Model Mesh, and

e) Sustainable & Green AI.

How to Become an AI and Machine Learning Specialist After 12th?

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