Artificial Intelligence (AI):
AI is a branch of computer science that focuses on creating systems and machines that can perform tasks that typically require human intelligence, such as problem-solving, decision-making, speech recognition, and language understanding.

Machine Learning (ML):
ML is a subset of AI that involves the development of algorithms and models that allow computers to learn from and make predictions or decisions based on data. It is a key component of many AI application.

Machine Learning Engineer:
Role: Develop and implement ML algorithms and models.
Duties: Data preprocessing, model selection, training, and deployment. They work on improving model performance and efficiency.

Data Scientist:
Role: Analyze and interpret complex data to solve business problems.
Duties: Data collection, cleaning, exploratory data analysis, building predictive models, and providing actionable insights.

AI Research Scientist:
Role: Conduct research in AI and ML to advance the field's knowledge.
Duties: Develop novel algorithms, publish research papers, and collaborate with academic institutions or industry labs.

AI/ML Software Developer:
Role: Build software applications and systems that leverage AI and ML capabilities.
Duties: Design, develop, and maintain software that integrates AI/ML models, often in the context of applications like recommendation systems or chatbots.

AI Ethics and Compliance Officer:
Role: Ensure that AI systems are developed and used ethically and in compliance with regulations.
Duties: Develop AI ethics guidelines, monitor AI deployments for fairness and transparency, and advise on regulatory compliance.

AI Project Manager:
Role: Oversee AI and ML projects from conception to deployment.
Duties: Coordinate teams, manage resources, set project goals, and ensure projects are delivered on time and within budget.

AI Solutions Architect:
Role: Design AI and ML solutions that address specific business problems.
Duties: Assess business needs, select appropriate AI technologies, and design the overall architecture of AI systems.

Natural Language Processing (NLP) Engineer:
Role: Specialize in NLP, which deals with text and language-based data.
Duties: Develop NLP models for tasks like sentiment analysis, language translation, and chatbots.

Computer Vision Engineer:
Role: Focus on computer vision, which involves processing and understanding visual data.
Duties: Develop applications for image and video analysis, such as facial recognition or object detection.

AI Trainer or Annotation Specialist:
Role: Annotate and curate data used for training AI models.
Duties: Label and preprocess training data to improve model accuracy.

Step 1:  Choose the Right Stream:  For your 10+2, opt for a science stream, which typically includes subjects like mathematics, physics, and computer science. This will lay the foundation for a career in AI and ML.

Step 2:  Pursue a Bachelor's Degree:  Enroll in a bachelor's degree program related to computer science, data science, artificial intelligence, or machine learning. Some popular options include Bachelor of Technology (B.Tech) or Bachelor of Science (B.Sc.) in Computer Science, Data Science, or Artificial Intelligence. 

During your undergraduate studies, pay special attention to mathematics, particularly linear algebra, calculus, and statistics. Strong math skills are crucial for understanding AI and ML algorithms.

Develop your programming skills in languages like Python, which is widely used in AI and ML.

Step 3:  Postgraduate Studies (Optional):  Consider pursuing a master's degree in AI, ML, or a related field for more advanced knowledge and specialization. Several Indian universities offer these programs.

Step 4:  Certifications: Obtain relevant certifications from organizations like Google, AWS, or Microsoft to validate your skills.

Becoming a professional in AI and ML in India requires dedication and continuous learning. Keep in mind that the field is highly competitive, so demonstrating your passion, skills, and dedication through your education, projects, and experience is key to success.

Data Scientist
Machine Learning Engineer
AI Research Scientist
Natural Language Processing (NLP) Engineer
Computer Vision Engineer
AI Consultant
AI Solutions Architect
AI Product Manager
AI Ethics and Compliance Officer
AI Trainer or Data Annotator
AI Project Manager
AI/ML Research Engineer
AI Analyst
AI Developer/Software Developer
Deep Learning Engineer
AI Security Analyst

Technology and Software Development
Healthcare and Life Sciences
Finance and Banking
E-commerce and Retail
Automotive and Transportation
Manufacturing and Robotics
Gaming and Entertainment
Government and Defense
Agriculture and Farming
Education and EdTech
Energy and Utilities
Marketing and Advertising
Natural Language Processing (NLP) Applications
Computer Vision and Image Processing
Cybersecurity
Research and Academia

The salary and perks in AI and ML are attractive, with variations based on factors like location, experience, and role. On average:

• Entry-level salaries: ₹4-10 lakhs per annum.
• Experienced professionals: ₹15-50+ lakhs per annum.
• Specialized roles (e.g., AI Research Scientists): ₹30-80+ lakhs per annum.
• Benefits often include bonuses, stock options, flexible work arrangements, and opportunities for research and innovation.