How to become AI Engineer after 10th?

To become an AI Engineer after 10th: 1) Complete 12th with PCM (Physics, Chemistry, Math), 2) Get B.Tech in Computer Science/AI/ML, 3) Learn programming (Python, R), 4) Study machine learning and deep learning, 5) Build AI projects, 6) Get internships. BecomeWho provides complete step-by-step roadmap for AI Engineer career.

How to become a Data Scientist in India?

To become a Data Scientist: 1) Get degree in Statistics/Math/Computer Science, 2) Learn Python/R programming, 3) Master statistics and machine learning, 4) Learn SQL and data visualization, 5) Build portfolio projects, 6) Get certified, 7) Apply for jobs. Average salary: ₹6-25 LPA. BecomeWho offers free roadmap.

How to become a Software Engineer?

To become a Software Engineer: 1) Learn programming languages (Java, Python, JavaScript), 2) Get B.Tech/BCA or self-learn, 3) Build projects and portfolio, 4) Learn frameworks and tools, 5) Practice coding problems, 6) Apply for internships, 7) Get job. Entry salary: ₹3-8 LPA. Follow BecomeWho's free roadmap.

How to become a Lawyer in India?

To become a Lawyer: 1) Complete 12th in any stream, 2) Clear CLAT exam, 3) Get LLB (3 years) or BA LLB (5 years), 4) Register with Bar Council, 5) Start practice or join law firm. Lawyer salary: ₹2-50 LPA depending on experience and specialization.

How to become a Paralegal in India?

To become a Paralegal: 1) Complete 12th, 2) Get paralegal certificate/diploma, 3) Learn legal research and documentation, 4) Gain experience in law firms, 5) Specialize in specific law areas. Paralegal salary: ₹2-6 LPA. No law degree required.

BecomeWho is India's leading platform for career roadmaps. We provide expert-vetted, step-by-step guides on how to become Frontend Developer, Backend Developer, Full Stack Developer, AI/ML Engineer, Product Manager & UI/UX Designer. All roadmaps are completely free with salary insights for Indian job market.

How much does a AI Engineer earn in India?

AI Engineer salary in India ranges from ₹5 - ₹12 LPA (entry-level/associate AI engineer) for entry-level to ₹20 - ₹60+ LPA (senior ML/AI engineer, lead, research applied roles) for senior positions. Strong demand in product companies, startups (GenAI, fintech, healthtech), and research labs in Bangalore, Hyderabad, Pune and NCR — high growth for engineers who can ship models to production.

How long does it take to become a AI Engineer?

It typically takes 1.7 - 4.7 years (self-paced, project-focused) to become a AI Engineer, depending on your starting point and dedication. Our roadmap is designed for Beginner → Advanced level learners.

What skills are required for AI Engineer?

Key skills for AI Engineer include: Essential Math for ML, Python for Data & ML, Intro to Machine Learning (classical), Frameworks: PyTorch & TensorFlow (choose one, learn both eventually), Core DL Topics: CNNs, RNNs, Transformers, Attention, Data engineering essentials for ML, Experiment Tracking & Model Versioning, Model serving & inference patterns. Our roadmap covers all essential skills step-by-step.

Is the AI Engineer roadmap free?

Yes, our AI Engineer roadmap is completely free. You get access to the full step-by-step guide, resources, and progress tracking without any cost.

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Become a AI Engineer

Artificial Intelligence & MLBeginner → Advanced1.7 - 4.7 years (self-paced, project-focused)

Overview

A practical, India-centric AI Engineer roadmap that takes learners from math & ML basics through production-grade model engineering and deployment. It emphasizes hands-on projects, MLOps, ethics, and domain specialization. Every paid course suggestion includes an explicit free alternative so learners never get blocked by paywalls.

Salary Range

₹5 - ₹12 LPA (entry-level/associate AI engineer) - ₹20 - ₹60+ LPA (senior ML/AI engineer, lead, research applied roles)

Job Outlook

Strong demand in product companies

Role Archetype

A curious engineer who blends math, software engineering and product-sense; automates workflows, measures model behavior, and communicates trade-offs to cross-functional teams.

Roadmap Phases

Phase 1

Phase 1 — Foundations: Math, Python & ML Basics

Build the mathematical intuition (linear algebra, probability, statistics), Python skills, and core ML basics (supervised learning, model evaluation).

1.1

Essential Math for ML

Learn

Linear algebra (vectors, matrices), calculus basics (gradients), probability and statistics (distributions, expectations, hypothesis testing).

1.2

Python for Data & ML

Learn

Numpy, Pandas, Matplotlib/Seaborn, and basic scripting: data cleaning, EDA and reproducible notebooks.

1.3

Intro to Machine Learning (classical)

Learn

Supervised vs unsupervised methods, evaluation metrics, cross-validation, bias-variance tradeoff and feature engineering.

Mark all 3 steps complete to unlock Next Phase(0/3)

Help us refine this roadmap

Suggest an improvement or missing step

← Back

Become a AI Engineer

Artificial Intelligence & MLBeginner → Advanced1.7 - 4.7 years (self-paced, project-focused)

Overview

Salary Range

₹5 - ₹12 LPA (entry-level/associate AI engineer) - ₹20 - ₹60+ LPA (senior ML/AI engineer, lead, research applied roles)

Job Outlook

Strong demand in product companies

Role Archetype

A curious engineer who blends math, software engineering and product-sense; automates workflows, measures model behavior, and communicates trade-offs to cross-functional teams.

Roadmap Phases

Phase 1

Phase 1 — Foundations: Math, Python & ML Basics

Build the mathematical intuition (linear algebra, probability, statistics), Python skills, and core ML basics (supervised learning, model evaluation).

1.1

Essential Math for ML

Learn

Linear algebra (vectors, matrices), calculus basics (gradients), probability and statistics (distributions, expectations, hypothesis testing).

1.2

Python for Data & ML

Learn

Numpy, Pandas, Matplotlib/Seaborn, and basic scripting: data cleaning, EDA and reproducible notebooks.

1.3

Intro to Machine Learning (classical)

Learn

Supervised vs unsupervised methods, evaluation metrics, cross-validation, bias-variance tradeoff and feature engineering.

Mark all 3 steps complete to unlock Next Phase(0/3)

Help us refine this roadmap

Suggest an improvement or missing step