How to Become an AI Engineer After 12th or Graduation

Artificial Intelligence (AI) is a field that combines programming, data and machine learning. If you want to build a career in this field, learning the right skills in a planned order can help you get started.

Learners can first develop basic programming skills and then advance to data analysis, machine learning methods and Generative AI applications. Students and graduates can use this approach to build their skills and prepare for roles related to AI and data.

What Does an AI Engineer Do?

An AI engineer works with AI-related tools and technologies. The learning journey covers programming, data analytics, machine learning and Generative AI. These areas also connect to other career options in data and technology.

Key Responsibilities of an AI Engineer

A learning path towards AI and data roles can include:

• Learning Python programming.

• Working with data using analytics tools.

• Using SQL and building dashboards.

• Studying machine learning concepts.

• Learning about Generative AI, prompt engineering and practical AI tools.

AI Engineer vs Data Professional

AI Engineer and Data Professional are related career paths, but they can lead to different roles. The learning pathway covers the following career options:

Who Can Become an AI Engineer?

Students from different educational backgrounds can start building skills for AI and data-related careers. The AI Engineer programme includes college students, fresh graduates and working professionals who want to move into AI and data roles.

AI Career Options After BTech, BCA and MCA

The AI and Data Professional learning pathway is designed for students, graduates and working professionals who want to develop skills in AI and data-related fields.

• B.Tech and B.E. students from all branches

• BCA and MCA students

• B.Sc. students in Computer Science or IT

• Final-year students

• Fresh graduates

• Working professionals looking to transition into AI and data roles

These learners can work towards career options such as AI Engineer, Data Analyst, BI Analyst, ML Engineer and GenAI Associate. If you are also interested in software development, explore the PW SkillWallah SDE with AI programme to learn about its programming, web development and full-stack learning pathway.

Can Beginners Learn AI Without Coding Experience?

Yes, beginners can start learning AI without prior coding experience through a structured learning path. The programme begins with Python basics and progresses to more advanced AI concepts.

Starting with the basics helps learners build their programming knowledge before progressing to more advanced topics.

Skills Required to Become an AI Engineer

An organised learning path helps build skills in Python, SQL, data analytics, machine learning and Generative AI step by step.

1. Python Programming Fundamentals

Python is an important part of the learning path. Begin with core Python skills, then build your knowledge of more advanced programming concepts. This stage builds the programming foundation needed for the next learning levels.

2. SQL, Data Analytics and Visualisation

After Python, learn SQL and business intelligence. This stage includes SQL fundamentals, advanced SQL and dashboarding.

You can then move to data analytics, including:

• NumPy

• Pandas

• Data visualization

These topics form part of the learning path for data-related roles.

3. Machine Learning and Generative AI

Once you have covered the earlier topics, progress to machine learning and Generative AI.

Machine learning includes classical machine learning. The Generative AI module focuses on prompt engineering, AI applications and the use of Generative AI tools.

Step-by-Step AI Engineer Learning Roadmap

A structured roadmap helps you learn the topics in a clear order. The following stages follow the AI and Data Professional programme's learning sequence.

1. Start With Excel and Python

Begin with Microsoft Excel to build your productivity and analytics foundation. Then move to Python fundamentals and advanced Python.

The programme assigns one month to Excel and two months to Python programming.

2. Learn SQL and Business Intelligence

Next, study SQL fundamentals, advanced SQL and dashboarding. This stage focuses on working with databases and presenting information through dashboards.

The programme assigns three months to this level.

3. Progress to Data Analytics, ML and GenAI

After SQL and business intelligence, follow these learning stages:

The programme runs for around 12 months and combines live sessions, recorded lessons and practical lab work.

The programme also supports career preparation through resume development, LinkedIn profile improvement, portfolio creation, aptitude and verbal practice, and mock technical and HR interviews. It also lists placement assistance, but it does not guarantee placement. The final certification listed is PW Certified AI Engineer & Data Professional.

Becoming an AI Engineer involves building skills in Python, SQL, data analytics, machine learning and Generative AI through a structured learning path. With consistent practice and preparation, learners can work towards AI and data-related career opportunities.