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Artificial Intelligence - AI Courses

Artificial Intelligence helps systems learn from data without being directly programmed. In an online Artificial Intelligence course, you’ll learn how to build models, train neural networks, and design applications that improve over time. These skills open up opportunities in AI.

Learn from faculty at globally top-ranked universities

Earn an average salary hike of 51% after completion

Artificial Intelligence & Machine Learning - AI ML Courses

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Free AI Courses: Start Learning For Free

Start your AI/ML journey with our free online AI courses for beginners and build your foundational knowledge for advanced learning.

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ChatGPT for Developers

Free Certificate

ChatGPT for Developers

Learn to harness the power of ChatGPT! Improve your productivity by making ChatGPT your personal coding assistant. Automate repetitive tasks like testing, other maintenance tasks and learn how to use ChatGPT APIs.

2 Hours

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Free Certificate

Introduction to Generative AI

What is Generative AI? Why has it recently become a buzzword? Dive deeper into the Generative AI landscape, its evolution over the years, its potential impact on industries, jobs, use cases and the skills you need to develop to succeed in the Generative AI era.

2 Hours

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Free Certificate

Intro to Natural Language Processing

This course on Artificial Intelligence will help in taking your first step towards learning the interactions between human language and computers i.e., NLP. The course covers the basics of NLP, and other topics such as RegEx for building tools for Spell Correction, Phonetic Hashing, and Spam Detection

11 Hours

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Free Certificate

Adv Prompt Engineering with ChatGPT

Ever wondered how AI-powered chatbots understand and respond to your questions? Join our course on Advanced Prompt Engineering with ChatGPT to craft effective prompts that enable ChatGPT to provide accurate and helpful responses. Discover the art of optimizing prompts, mastering conversational flow, and empowering ChatGPT to engage in meaningful and natural conversations, opening doors to enhanced customer support, virtual assistants, and more.

2 Hours

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Free Certificate

Fundamentals of Deep Learning of Neural Networks

Harness the power of ChatGPT and improve your productivity by making ChatGPT your personal coding assistant who can Automate repetitive tasks.

28 Hours

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Free Certificate

Linear Algebra for Analysis

Learn about vectors, linear transformations, matrices, eigenvalues and eigenvectors in Linear Algebra as you build a solid foundation for analytics with this course

5 Hours

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Free Certificate

Advanced SQL: Functions and Formulas

Improve your understanding of SQL as you learn about window functions, partitioning, query optimisation, case statements, stored functions & more in this course

11 Hours

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Free Certificate

Hypothesis Testing Crash Course

Learn about the various types of hypotheses, Decision-making criteria, critical value and p-value methods for testing Hypothesis.

11 Hours

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Free Certificate

Basics of Inferential Statistics

This data analytics course will help you learn how to use a random sample data to describe and make inference about the population.

15 Hours

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Free Certificate

Unsupervised Learning: Clustering

Learn the fundamentals of clustering in unsupervised learning as you introduce yourself to Clustering, K-Means Clustering Hierarchical Clustering, and its execution

11 Hours

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Free Certificate

Logistic Regression for Beginners

The course covers the concept of Logistic Regression and its applications in the industry.

17 Hours

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Free Certificate

Linear Regression - Step by Step Guide

Learn the basics of simple and multiple linear regression, and their relevance in various industries.

21 Hours

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Best-in-class content by leading faculty and industry leaders in the form of videos, cases and projects, assignments and live sessions
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Our Top University Partners

Know All About The Partnered Universities

upGrad has partnered with the leading universities listed below to offer some of the most advanced and in-demand AI courses aligned with the latest industry trends.

1. IIIT Bangalore

IIIT Bangalore offers 12 programs across undergraduate and postgraduate levels, giving students a wide range of choices including Artificial Intelligence & Data Science (AI&DS), Computer Science & Engineering (CSE), and Electronics & Communication Engineering (ECE).

For more detailed insights, explore the complete IIIT Bangalore Overview.

2. University of Maryland

University of Maryland offers 264 programs across undergraduate and graduate levels, giving students a wide range of choices including the Bachelor of Science in Computer Science, the Master of Science in Artificial Intelligence (MSAI), the M.Eng. in Engineering Artificial Intelligence (PMAI), and the Master of Science in Applied Machine Learning (SAML).

For more detailed insights, check out the University of Maryland Overview.

3. Golden Gate University

Golden Gate University offers 60+ degrees and certificates, including the Master of Science in Artificial Intelligence (MSAI) and the Doctor of Business Administration (DBA) in Emerging Technologies with a focus on Generative AI. Students can also take specialized courses such as AI Ethics and Governance, Prompt Engineering and Validation, and Agentic AI.

For more detailed insights, check out the Golden Gate University Overview.

4. Liverpool John Moores University

Liverpool John Moores University offers over 250 courses, including the BSc (Hons) Computer Science with Artificial Intelligence, the MSc Artificial Intelligence (Machine Learning), and the LLM Artificial Intelligence and Law. Online options include the MS in Machine Learning & AI with specializations like Generative AI and MLOps.

For more detailed insights, check out the Liverpool John Moores University Overview.

Artificial Intelligence (AI) Course Projects: Learn by Doing

17+

Projects

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In this assignment, you will work for a consumer finance company which specialises in lending various types of loans to urban customers and use EDA to analyse the patterns present in the data. This will ensure that the applicants are capable of repaying the loan and are not rejected.

Credit EDA Assignment

Credit EDA Assignment

In this assignment, you will work for a consumer finance company which specialises in lending various types of loans to urban customers and use EDA to… Know More

Telecom companies often face the problem of churning customers due to the competitive nature of the industry. Help a telecom company identify customers that are likely to churn and make data-driven strategies to retain them from the perspective of a business analyst.

Model Selection Case Study -Telecom Churn

Model Selection Case Study -Telecom Churn

Telecom companies often face the problem of churning customers due to the competitive nature of the industry. Help a telecom company identify customer… Know More

Face Mask Detection

Face Mask Detection

Create a custom object detector using the YOLO algorithm to detect the presence of face masks in the images of different people. 

Machine Translation System

Machine Translation System

You will build an attention based neural machine translation model translating from one language to another. 

Build a Model for converting MRI images from one type (T1) into other (T2) and vice versa. CycleGAN model is used for producing T2 type MRI images given T1 type input MRI images.

Style Transfer using GAN's

Style Transfer using GAN's

Build a Model for converting MRI images from one type (T1) into other (T2) and vice versa. CycleGAN model is used for producing T2 type MRI images gi… Know More

Predict the sales for a european pharma giant using a host of different types of variables. Apply VAR and VARMAX models to build the appropriate model.

Sales Forecasting

Sales Forecasting

Predict the sales for a european pharma giant using a host of different types of variables. Apply VAR and VARMAX models to build the appropriate mode… Know More

Build a sentiment analysis based product recommendation system to recommend the similar products to the users. Sentiment analysis is used to fine tune the product recommendation system.

Sentiment analysis based Product Recommender system

Sentiment analysis based Product Recommender system

Build a sentiment analysis based product recommendation system to recommend the similar products to the users. Sentiment analysis is used to fine tune… Know More

Eye for the Blind

Eye for the Blind

Build a model that can help any visually impaired person in understanding image present before them. 

Custom Entity detection in Healthcare data

Custom Entity detection in Healthcare data

You will build a custom NER to get the list of diseases and their treatment from a medical healthcare dataset. 

Learners will use the Markov Decision Process & Q-Learning to build an RL agent that learns to choose the best request so as to maximise the total profit earned by the agent that day.

Maximising profit of cab driver using RL

Maximising profit of cab driver using RL

Learners will use the Markov Decision Process & Q-Learning to build an RL agent that learns to choose the best request so as to maximise the total pro… Know More

Build a model to using the concepts of natural language processing and recommender systems to recommend news stories to users on a popular news platform.

News Recommender System

News Recommender System

Build a model to using the concepts of natural language processing and recommender systems to recommend news stories to users on a popular news platfo… Know More

Gesture Recognition

Gesture Recognition

Make a Smart TV system which can control the TV with user’s hand gestures as the remote control  

Melanoma Detection Assignment

Melanoma Detection Assignment

Build a neural network from scratch in Tensorflow to identify the type of skin cancer from image. 

Train an agent to play Tic Tac Toe

Train an agent to play Tic Tac Toe

Learners will apply Q-Learning to train an RL agent to play the game of numerical Tic Tac Toe. 

Classification of customer complaints

Classification of customer complaints

Create a solution that will help in identifying the type of complaint ticket raised by the customers of a multinational bank 

To create an ML system that can predict the propensity of customers cancelling the subscription plan. The aim of the project is to provide the marketing team with insights into why a customer is choosing to leave. This will assist in identifying the probability of customer churn in the future so that preventive action can be taken.

Customer Churn prediction

Customer Churn prediction

To create an ML system that can predict the propensity of customers cancelling the subscription plan. The aim of the project is to provide the market… Know More

Advanced Regression

Advanced Regression

Build a regularised regression model to understand the most important variables to predict. 

Understand the factors that drive the Airbnb business and help the team leads tackle problems and bottlenecks through extensive data analysis on UI tools.

Airbnb Case Study

Airbnb Case Study

Understand the factors that drive the Airbnb business and help the team leads tackle problems and bottlenecks through extensive data analysis on UI to… Know More

Artificial Intelligence Course Instructors: Learn From The Best

8

Instructors

8

Industry Experts

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Dr. Atif Waraich

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Faculty - Computer Science, LJMU

A Senior faculty of Engineering and Technology at LJMU who has multiple publications in the health care domain 

LJMU Profile
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Prof. Dhiya Al-Jumeily

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Faculty: Faculty of Engineering and Technology

A senior member of the IEEE and a chartered IT Professional, he is a fellow of the UK Higher Education ACademy 

LJMU Profile
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Tricha Anjali

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Ex-Associate Dean, IIITB

Prof. Anjali has a PhD from Georgia Institute of Technology as well as an integrated MTech (EE) from IIT Bombay. 

LinkedIn ProfileLinkedin
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Prof. Paulo Lisboa

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Head of Dept - Applied Mathematics, LJMU - Retired

Studied mathematical physics at LU and was the chairman of Industrial Mathematics at KMJU in 1996 and Head of Graduate School in 2002 

LJMU Profile
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Prof. G. Srinivasaraghavan

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Professor, IIITB

Prof. Srinivasaraghavan has a PhD in Computer Science from IIT-K and 18 years of experience with Infosys and several other MNCs. 

IIITB Profile
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Debabrata Das

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Director, IIITB

Dr. Debabrata Das is Director of IIITB. He has received his PhD from IIT-KGP. His main areas of research are IoT and Wireless Access Network 

IIITB Profile
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Chandrashekar Ramanathan

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Dean Academics, IIITB

Prof. Chandrashekar has a PhD from Mississippi State University and experience of over 10 years in several multinational organisations. 

IIITB Profile
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Dr. Gabriela Czanner

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Faculty - Engineering and Technology, LJMU

A Senior lecturer at Department of Applied Mathematics at LJMU. Her research focus is advanced statistics for decision support 

LinkedIn ProfileLinkedin

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Industry Mentors

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Success Stories: What Our Learners Have To Say

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Worth the price pursuing

Though I have been in the Analytics and ML space for a few years now, the programme curriculum I went through did help me tremendously during the interview process

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Sagar Pavan

Lead Data Scientist, Craftt

10 Years of Experience

Program curriculumn helped me in excellence

20 months Master of Science program on ML and AI, conducted by IIIT, Bangalore and LJMU, UK. This double degree program is managed by UpGrad Online learning platform.

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Angshuman Mukherjee

Principal Architect, LTIMindtree

23 Years of Experience

Makes you ready for the industry

A Master's degree will not only give you the edge but also enables you to prepare for the job market

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Samarjit Adhikari

Sr. Principal Software Engineer, Incedo

19 Years of Experience

This would not be an achievement without upGrad and IIITB

I am excited to start my first job with Ugam as Associate Analyst and this wouldnt be an achievement without upGrad and IIITB. Thanks to the team! March 2021 is the month of celebration and I believe new colours will now be a part of my new journey too. Wish you all a safe and happy holi!

LinkedInlinkedinMar 1, 2021
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Sakshi Maharana

Associate Analyst

9 Years of Experience

Thanks to upGrad for giving me the platform, knowledge and opportunity to apply for the job!

I am pleased to announce that I have joined CitiusTech as a Senior Software Engineer in the role of AI Engineer. I would like to thank upGrad and upGrad Placements for giving me the platform, knowledge and opportunity to apply for the job. Thank you Argha Mukherjee for your guidance and support during and post my job offer! You are really helpful and patient and I look forward to working with you. Thanks Udit Pathak for being so patient with all my questions and your suggestions!

LinkedInlinkedinOct 2, 2021
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Arpan Chattopadhyay

Senior Software Engineer - AI Engineer

8 Years of Experience

AI Course Blogs: You Might Like To Read

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24 Exciting IoT Project Ideas & Topics For Beginners 2025 [Latest]

Looking for IoT Project Ideas? Start off with these cool IoT project ideas to test your strengths & weakness but also help you to gain exposure that can be helpful for boosting your career.

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Kechit Goyal

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Top 16 Artificial Intelligence Project Ideas & Topics for Beginners [2025]

Looking for Artificial Intelligence Project Ideas? Start off with these cool AI project ideas to test your strengths & weakness but also help you to gain exposure that can be helpful for boosting your career.

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Pavan Vadapalli

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Basic CNN Architecture: Explaining 5 Layers of Convolutional Neural Network

Did you know that you can classify or analyze images within a few lines of code using CNN? Check out this article that explains the Convolutional Neural Network architecture explaining its 5 layers.

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MK Gurucharan

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Are you curious to learn more about chatbot using Python and how to make chatbot in python? We’ll take a step by step approach and break down the process of building a Python chatbot.

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6 Types of Regression Models in Machine Learning You Should Know About

If you are new to machine learning, check out this article to learn 6 different types of regression in machine learning, under what condition each of them can be used and understand the regression modeling concept.

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Pavan Vadapalli

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Top 7 Challenges in Artificial Intelligence in 2025

Artificial Intelligence has a lot of potentials. But, do you know the issues surrounding the field? Read below to find out about the challenges in AI.

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Pavan Vadapalli

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Why Understanding Artificial Intelligence Matters Today?

Artificial Intelligence is driving innovation across industries: from finance and healthcare to education and marketing. Companies today seek professionals who can leverage AI to solve problems, improve efficiency, and enhance customer experiences. That’s why AI has become one of the most in-demand skills globally.

Learning AI today is like learning coding in the early 2000s; it opens doors to a wide range of future-proof careers. Even if you’re not from a tech background, starting with a beginner-friendly Artificial Intelligence course can help you understand the core logic and tools used by AI professionals.

Top Reasons to Pursue an AI Course in 2025

AI is the backbone of the next industrial revolution. 2025 is the best time to be part of it. Here are some reasons why you should learn Artificial Intelligence in 2025.

Reason

Description

AI Powers Every Industry

AI is transforming healthcare, finance, marketing, and education by automating and optimizing everyday processes.

Rising Demand, Limited Talent

AI job roles are growing rapidly, but skilled professionals remain scarce, making it the right time to upskill.

High-Paying Career Opportunities

Roles like ML Engineer, Data Scientist, and AI Product Manager offer top-tier salaries and growth potential.

Future-Proof Your Career

As automation increases, AI knowledge helps you stay relevant and lead in the age of intelligent systems.

Smarter Business Decisions

AI enables faster, data-backed insights that drive innovation and improve business performance.

Endless Innovation & Research

Emerging fields like Generative AI, NLP, and Robotics offer vast opportunities for exploration and discovery.

Open to Non-Tech Professionals

With user-friendly tools and guided learning, even non-coders can apply AI in their domains.

Ethical & Responsible AI

Learning AI helps you build systems that are fair, transparent, and socially responsible.

Who Can Pursue an Artificial Intelligence Course?

Understanding Artificial Intelligence might sound complex, but here’s the good news: you don’t need to be a genius coder or mathematician to start learning it. What truly matters is curiosity, logical thinking, and a willingness to solve problems using data and algorithms.

Eligibility for Artificial Intelligence Course

The eligibility criteria for Artificial Intelligence courses largely depend on the type of program you choose, whether it’s a degree course, a professional certification, or an online program. However, most AI courses have some common requirements:

  1. Educational Background:
    • For undergraduate programs, you typically need to have completed 10+2 with Mathematics as one of the core subjects.
    • For postgraduate or advanced programs, a bachelor’s degree in Computer Science, Engineering, Mathematics, Statistics, or related fields is often preferred.
  3. Basic Programming Knowledge: While not mandatory for all beginner courses, having a basic understanding of programming languages like Python or R can make learning easier.
  4. Analytical & Problem-Solving Skills: Since AI involves data analysis, pattern recognition, and logical reasoning, strong analytical skills can help you grasp complex topics faster.
  5. Mathematical Foundations: A basic understanding of linear algebra, probability, and statistics is beneficial. But don’t worry, upGrad’s beginner-friendly Artificial Intelligence online courses start by revisiting these fundamentals before moving on to advanced topics.

How to Choose the Best Artificial Intelligence Course

With so many AI programs available today, picking the right one can feel overwhelming. Whether you’re looking for artificial intelligence online courses or full-fledged artificial intelligence degree courses, choosing wisely ensures you get the skills, experience, and career support you need.

1. Check the Course Curriculum

A strong AI program should cover both theory and practical applications. Look for a syllabus that includes:

  • Machine Learning & Deep Learning
  • Neural Networks & Natural Language Processing
  • Computer Vision & Robotics
  • AI Tools, Frameworks, and Programming Languages (Python, R, TensorFlow, PyTorch)
  • Real-world projects and case studies

2. Evaluate the Learning Format

  • Online AI Courses: Flexible, self-paced, and suitable for working professionals or students.
  • Offline/On-Campus Programs: Immersive and structured, with direct access to faculty and peers.
  • Hybrid Programs: Combine the flexibility of online learning with the benefits of live mentorship and workshops.

3. Consider the Faculty and Mentorship

The quality of instructors matters. Learning from industry experts and mentors ensures you gain insights beyond textbooks, practical tips, industry trends, and guidance on real-world projects.

4. Look for Career Support

A strong AI program doesn’t just teach concepts, it helps you start a career. Check if the course offers:

  • Resume and LinkedIn profile support
  • Interview preparation
  • Capstone projects that can be showcased in your portfolio

5. Accreditation and Recognition

Whether it’s a degree course or an online certification, verify that the program is recognized by industry professionals or reputed universities. This adds credibility to your resume and enhances employability.

6. Reviews and Alumni Success

Read testimonials, case studies, and alumni success stories. A program with proven outcomes is more likely to deliver the skills and job opportunities it promises.

Artificial Intelligence Course Syllabus Breakdown: What You Will Learn

Choosing the right Artificial Intelligence course isn’t just about the name or fees; the syllabus is what truly determines what you’ll learn and how prepared you’ll be for real-world AI roles. Before enrolling in any artificial intelligence course, it is essential to review the syllabus. This will help you make an informed decision.

1. Core Programming and Tools

  • Python and R Programming: The most widely used languages in AI for building algorithms and models.
  • Libraries and Frameworks: NumPy, Pandas, TensorFlow, Keras, and PyTorch.
  • Version Control & Git: Essential for collaborative AI projects.

2. Machine Learning

  • Supervised and Unsupervised Learning: Building predictive models from data.
  • Regression, Classification, and Clustering: Core techniques for real-world applications.
  • Evaluation Metrics: Measuring model performance accurately.

3. Deep Learning

  • Neural Networks: Understanding how machines “learn” patterns.
  • Convolutional Neural Networks (CNN): Key for image recognition and computer vision.
  • Recurrent Neural Networks (RNN) & LSTM: Useful for sequential data like text or speech.

4. Natural Language Processing (NLP)

  • Sentiment Analysis, Text Classification, and Language Translation
  • Chatbots and Conversational AI
  • Pretrained Models like BERT and GPT

5. Computer Vision

  • Image and Video Processing
  • Object Detection and Recognition
  • Applications in healthcare, autonomous vehicles, and security

6. Data Handling and Analytics

  • Data Preprocessing and Cleaning
  • Exploratory Data Analysis (EDA)
  • Feature Engineering and Selection

7. AI Ethics and Best Practices

  • Responsible AI and Bias Mitigation
  • Privacy, Security, and Ethical Considerations
  • Regulatory Guidelines in AI

8. Capstone Projects

Hands-on projects consolidate learning, such as:

  • Predicting stock market trends using ML models
  • Building a recommendation system
  • Image classification or object detection projects

Artificial Intelligence Career Opportunities and Job Roles

Completing an Artificial Intelligence course opens up a world of career possibilities and future scope. AI is transforming every industry, from healthcare and finance to retail, logistics, and entertainment. With organizations increasingly relying on AI-driven solutions, professionals with the right skills are in high demand.

1. Popular AI Job Roles

Job Roles

Job Description

Salary Range (in INR)

Machine Learning Engineer

Design and deploy ML models to solve real-world problems.

15-25 LPA

Data Scientist

Analyze and interpret complex datasets to guide business decisions.

18-30 LPA

AI Research Scientist

Explore advanced AI techniques and develop innovative algorithms.

50 Lacs - 1 Crore

AI Product Manager

Bridge the gap between AI technology and business needs.

20-30 LPA

Business Intelligence Analyst

Leverage AI tools to generate actionable insights for organizations.

10-20 LPA

Source: Glassdoor, Pay Scale, Ambition Box

*Salary figures are approximate and may differ based on location, experience, and

2. Emerging Roles in AI

  • Natural Language Processing (NLP) Engineer: Build applications like chatbots, virtual assistants, and text analytics tools.
  • Computer Vision Engineer: Work on image and video analysis for industries like autonomous vehicles, healthcare imaging, and security.
  • Robotics Engineer: Develop AI-powered robotics solutions for automation and manufacturing.

3. AI Opportunities Across Industries

  • Healthcare: AI-driven diagnostics, drug discovery, and patient care.
  • Finance: Fraud detection, risk assessment, and algorithmic trading.
  • Retail & E-commerce: Personalized recommendations, inventory optimization, and customer insights.
  • Automobile & Transportation: Autonomous vehicles, traffic management, and logistics optimization.
  • Education & Research: AI-powered learning platforms, virtual tutors, and predictive analytics.

How to Get Placed After Completing an Artificial Intelligence Course

Completing an Artificial Intelligence course equips you with the technical skills needed for AI roles, but landing your first job or transitioning into a higher role requires strategic preparation. Here’s how to maximize your placement opportunities.

1. Build a Strong Portfolio

  • Work on real-world AI projects during your course to demonstrate your practical skills.
  • Include projects on machine learning, deep learning, NLP, and computer vision in your portfolio.
  • Highlight projects that solve industry-relevant problems. Employers value results-oriented experience.

2. Resume and LinkedIn Optimisation

  • Clearly mention your AI skills, certifications, and projects.
  • Use metrics to showcase impact, e.g., “Built a predictive model that improved sales forecasting accuracy by 15%.”
  • Highlight tools, programming languages, and frameworks you are proficient in.

3. Mock Interviews and Technical Assessments

  • Practice common AI interview questions, coding challenges, and case studies.
  • Participate in mock interviews offered by course providers or peer communities.
  • Focus on problem-solving and explaining your approach clearly; communication is as important as technical skill.

4. Leverage Mentorship and Career Support

  • Connect with industry mentors to gain insights into recruitment trends.
  • Seek guidance on customizing your applications for AI roles.
  • Career support teams often assist with interview scheduling, referrals, and networking opportunities.

5. Continuous Learning and Upskilling

  • Stay updated with emerging AI trends and technologies.
  • Learn specialized AI skills, such as reinforcement learning, advanced NLP, or computer vision, to stand out from other candidates.
  • Participate in hackathons, coding competitions, and online challenges to showcase expertise.

6. Networking and Community Engagement

  • Join AI communities, forums, and LinkedIn groups to connect with professionals.
  • Engage with alumni who can provide guidance or refer you to job opportunities.
  • Attend webinars, workshops, and industry events to expand your network.

Everything You Need to Know About Artificial Intelligence

Artificial Intelligence is transforming industries and creating exciting career opportunities. To help you build a strong foundation and advance your AI skills, we’ve compiled a list of curated resources covering AI fundamentals, applications, projects, courses, and career insights. These blogs are organized to guide you step by step, from understanding AI to exploring job roles and salary trends.

Frequently Asked Questions about AI Course

1. What is the difference between AI, ML, and Deep Learning?

Artificial Intelligence (AI) is the broader concept of machines being able to carry out tasks in a smart way. Machine Learning (ML) is a subset of AI that teaches machines to learn from data and improve over time without being explicitly programmed. Deep Learning is a further subset of ML that uses neural networks to simulate human decision-making. Think of it like this: AI is the big picture, ML is a key part of it, and Deep Learning is the high-powered engine that drives the most complex applications. If you’re interested in learning about machine learning, joining structured artificial intelligence classes or a machine learning course can help you build these skills step by step. 

2. How does machine learning work in real life?

Machine learning powers a lot of what you interact with every day. From personalized Netflix recommendations to fraud detection in banking, ML models learn from large datasets and adjust their outputs based on patterns. In short, it uses data to make smarter decisions, faster. Many classes for machine learning explain these real-world applications through case studies and projects.

3. What are the types of machine learning models?

There are mainly three: supervised learning (learning from labeled data), unsupervised learning (finding hidden patterns in unlabeled data), and reinforcement learning (learning from rewards and punishments through interaction with an environment). To learn these, you can explore a course of machine learning or structured machine learning classes that dive deep into each approach.

4. What are real-world examples of AI applications today?

Voice assistants like Siri and Alexa, self-driving cars, chatbots in customer service, medical image diagnostics, and even spam filters in your email are all real-world AI applications. Learners who take AI classes often work on projects that replicate these kinds of applications.

5. What is the future of AI and ML in India and globally?

With India’s digital economy expanding and global industries adopting AI at scale, the future looks promising. From smart cities to automated healthcare, AI/ML will be embedded in every aspect of our lives. The job market is booming, and now is the time to get skilled with an advanced artificial intelligence course.

6. What background knowledge is required to enrol in an AI and ML course?

Background knowledge in mathematics, particularly statistics, and some programming experience can be beneficial for enrolling in machine learning and AI courses. However, many programs, including the best Artificial Intelligence Course, are designed to cater to learners at different levels, including beginners.

7. Are there any prerequisites for the hardware or software required for the course?

Generally, learning about machine learning and AI requires a computer with sufficient processing power and internet connectivity. Specific software requirements, such as programming environments or data analysis tools, will depend on the course’s focus and are usually provided or recommended by the instructors. Flexible options like AI courses online make it easier to start without heavy technical requirements.

8. Can I learn AI/ML without a technical background?

Absolutely. While it helps to have a foundation in math or programming, many AI/ML programs today, including those by upGrad, are designed for non-tech learners too. You’ll start from the basics and gradually move to advanced concepts with plenty of guidance. For beginners, enrolling in an ai course or even options to learn artificial intelligence online can be a flexible way to start.

9.  Do I need to know coding to start an AI or ML course?

Not necessarily. Some beginner-level courses teach you coding (like Python) from scratch. However, if you’re aiming for intermediate or advanced programs, having some basic knowledge of programming will help. A structured AI intelligence course often guides you step-by-step.

10. Which programming language is best to start with for AI?

Python is the most popular language in the AI/ML world. It’s beginner-friendly, widely supported, and comes with powerful libraries like TensorFlow, Scikit-learn, and PyTorch.

11. How to learn AI and ML step-by-step?

Start with understanding the fundamentals of data and statistics, move to basic Python programming, then take up beginner-level courses in ML and AI. As you progress, take on small projects, participate in coding challenges, and explore specializations like NLP, computer vision, or deep learning. Many learners choose structured machine learning and ai courses or even advanced ai machine learning courses to deepen their expertise. 

12. What are the prerequisites for a machine learning course?

Most courses expect basic knowledge of math (especially linear algebra, probability, and statistics) and programming. But don’t worry, structured programs like upGrad’s often include these fundamentals to ease your learning curve. If you want a complete journey, an artificial intelligence and machine learning course is a great choice to build both sets of skills together.

13. How can AI & ML courses benefit businesses and industries?

Machine Learning AI courses can benefit businesses and industries by training professionals capable of implementing AI and ML solutions to improve efficiency, drive innovation, and create competitive advantages. Skills gained from these courses, such as data analysis and predictive modelling, are invaluable for businesses looking to leverage technology for growth and success.

14. Does upGrad offer machine learning with software engineering programs?

Yes, upGrad’s AI/ML programs integrate machine learning with software engineering, providing learners with first-hand experience in AI applications while mastering software development concepts, coding practices, and industry-relevant tools. Programs like the Executive PG in Applied AI and Generative AI for Software Development exemplify this blend.

15. How to compare AI/ML courses based on career goals?

Start by evaluating your background and your goals. If you’re switching careers, look for comprehensive programs. If you’re already in tech, choose specialized courses like NLP or Deep Learning. Make sure the course includes hands-on projects, expert mentorship, and an industry-aligned curriculum.

16.  What’s the difference between AI/ML certifications and full-time degrees?

Certifications are short, focused, and practical-ideal for working professionals. Degrees are longer, more academic, and can be expensive. If you want a faster career impact without quitting your job, a certification program like upGrad’s might be more suitable.

17. What should I look for in an AI/ML course curriculum?

Ensure the course covers basics (math, Python), core ML concepts, specializations (like NLP, computer vision), and real-world projects. Bonus points if it includes access to tools like TensorFlow, live sessions, and industry case studies.

18. Is there a difference between data science and AI/ML courses?

Yes. Data science is broader and includes data analysis, statistics, and visualization. AI/ML focuses more on algorithms that enable machines to make decisions. Some programs, like upGrad’s, combine both to give you a well-rounded learning experience.

19. Are there AI/ML courses with Python projects and real-world use cases?

Yes! UpGrad’s AI & ML programs include 17+ projects, including fraud detection, face mask detection, and churn prediction using Python and real datasets.


20. Which should I choose: Diploma in AI vs PG in AI programs?

Diploma programs in AI focus on practical, industry-ready skills and usually have shorter durations, making them ideal for professionals seeking hands-on experience quickly. PG programs in AI provide a deeper theoretical understanding, research opportunities, and broader academic recognition, suited for those aiming for advanced roles or long-term career growth in AI and ML.

21. Which are the best AI/ML training institutes online in India?

upGrad is recognized as one of the best AI/ML training institutes online in India, offering industry-aligned programs, live sessions, hands-on projects, and career support. Learners gain practical skills in AI, machine learning, and deep learning, with flexible online access to mentorship and placement assistance.

22. What are the artificial intelligence course fees in India?

Artificial Intelligence course fees in India vary depending on the program type, duration, and university affiliation. Short-term certification courses can start from ₹40,000, while advanced diploma or executive programs can range up to ₹5–10 lakhs. Fee structures often include mentorship, projects, and placement support, so it’s important to consider the overall value alongside the cost.

23. How do I choose the right artificial intelligence masters programs online for my career?

Selecting the best artificial intelligence master's programs online requires evaluating course curriculum, university recognition, industry projects, mentorship opportunities, and career support. Look for programs that teach advanced AI concepts like machine learning, NLP, and computer vision while offering flexible online learning, so you can gain both theoretical expertise and practical skills to accelerate your AI career.

24. Will I get mentorship and doubt support in the course?

Yes, that’s a key differentiator with upGrad. You get access to 1:1 mentorship from industry experts, regular doubt-clearing sessions, and feedback on your assignments.


25. Are there live classes or is it self-paced?

Most courses offer a hybrid model-self-paced modules along with live classes to clarify concepts and interact with peers. Perfect for balancing work and study.

26. What types of projects will I get to work on during the AI/ML course?

Expect to work on credit risk modeling, telecom churn prediction, face mask detection, NLP sentiment analysis, and more. These aren’t just theoretical assignments-you’ll build deployable solutions.

27. Are tools like TensorFlow, Keras, or ChatGPT part of the curriculum?

upGrad programs include hands-on training in tools like Python, TensorFlow, Keras, OpenCV, Hugging Face, GitHub Copilot, and many more

28. Can I balance this course with a full-time job?

Yes, that’s one of the biggest advantages. Courses are designed with working professionals in mind. You can learn at your own pace and join weekend or evening live sessions.


29. How can I estimate the total cost of pursuing an AI & ML course, including materials and other expenses?

To estimate the total cost of pursuing ML & AI certification courses, consider the tuition fees, cost of textbooks or software (if not included), and any other resources you may need. It's advisable to check the course details carefully to understand the detailed breakdown of costs.

30. How do online AI programs with industry projects help in gaining practical experience?

These programs provide hands-on exposure by letting learners work on real-world AI problems. Industry-aligned projects ensure that students not only understand theoretical concepts but also develop job-ready skills, build a strong portfolio, and enhance employability in AI and machine learning roles.

31. Is the AI/ML certificate recognized by employers?

Yes, especially when it’s from a platform like upGrad in partnership with universities like IIIT Bangalore, LJMU, or Microsoft. These certificates carry weight on your resume and LinkedIn.


32. What is the ROI of doing an AI/ML course in 2025?

Given the surge in AI adoption, ROI is strong. You could potentially see a salary hike, switch careers, or land international opportunities. Roles like AI Engineer or Data Scientist often start at ₹8 - 20 LPA in India and $100K+ abroad.


33. How does this course help in career transitions into AI/ML?

The program bridges skill gaps through real-world projects, domain exposure, and career support. You’ll also get interview prep, resume reviews, and access to hiring partners.

34. What is the career scope after AI & ML course in India?

The career scope after AI & ML course in India is vast, spanning roles like AI Engineer, Machine Learning Engineer, Data Scientist, and AI Product Manager. With rapid adoption of AI across industries such as healthcare, finance, e-commerce, and IT, certified professionals can expect high salaries, accelerated career growth, and opportunities to lead innovative AI projects.

35. Can someone get a job in AI/ML without a prior tech degree if they finish this course?

Yes! Many learners come from non-tech backgrounds and land AI/ML roles post-certification, especially with strong project portfolios and interview support provided by upGrad.

36. How do online diploma in artificial intelligence programs help build a career in AI?

Completing an online diploma in artificial intelligence program equips learners with essential skills like AI model development, data analysis, and machine learning deployment. upGrad provides industry-aligned content, mentorship, and career guidance to help students transition into AI roles with confidence.

37. How does experience affect the salary after AI & ML certification in India?

Experience significantly impacts the salary after AI & ML certification in India. Freshers in AI can earn approximately ₹5–6 LPA, mid-level professionals can command around ₹10 LPA, while highly experienced engineers may earn up to ₹50 LPA. Factors like industry, role, and skill set in sectors like finance, healthcare, and e-commerce can further influence compensation.

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  1. This program does not constitute a dual, joint, or twinning degree program

  1. upGrad does not grant credit; credits are granted, accepted or transferred at the sole discretion of an educational institution. upGrad is not a college or university i.