Learn AI with expert supervision and industry oriented curriculum. Artificial intelligence (AI) is no longer a futuristic concept confined to sci-fi novels or Hollywood blockbusters. Today, it is woven into the fabric of our everyday lives, curating playlists, suggesting movies, powering virtual assistants, and even helping diagnose diseases. For many, the idea to learn AI might feel overwhelming, like venturing into a world reserved for mathematics or tech geniuses.
But here is the truth: Artificial intelligence (AI) is more accessible than ever, and anyone with curiosity and determination can start their journey. This guide is designed to help beginners take their first steps into the fascinating world of Artificial intelligence (AI). Whether you are a student, a professional looking to future-proof your career, or simply someone intrigued by how machines learn to think, this blog will provide a clear and approachable roadmap to get started.
AI is not just about mastering algorithms or coding; it is about learning to think differently, solving problems creatively, and embracing the power of data.
How to Learn Artificial Intelligence Step-by-Step?
Learn Artificial intelligence (AI) with a step-by-step process and upskill yourself in the fields of automation, neural networks, and many more. Learning AI can be a rewarding and exciting journey. So the basic steps included in learning AI are mentioned below:
1. Understand the Basics
Basics include mathematics as well as programming. To learn AI, one must be fluent in linear algebra (including vectors, matrices, and transformations), calculus (including derivatives and integral optimizations), probability, and statistics. One also has to be comfortable with programming, primarily Python. Python is the most widely used language in AI. Learn about the different libraries that are used in AI implementations, including Pandas, NumPy, and Matplotlib.
2. Build a Strong Foundation in AI
To learn AI, we need to learn about AI and its foundations. AI includes Machine Learning and Deep Learning. Machine learning gives an understanding of supervised, unsupervised, and reinforcement learning. It includes various algorithms, including linear regression, decision trees, SVMs, and clustering that help in classification as well as clustering of the data. It involves heavy usage of Python libraries, including scikit-learn and XGBoost.
While deep learning provides an understanding of neural networks, backpropagation, and optimization. It includes architecture like convolutional neural networks (CNNs), RNNs, and transformers. Deep learning involves various frameworks, including TensorFlow and PyTorch.
3. Follow a Learning Path
Now that we have covered learning the basics and building an AI foundation, let us move towards how exactly we can move into the right path to learn AI.
One can follow different paths to learn AI, including online courses, books, videos, and tutorials. Books that can be used to learn AI include:
- “Hands-On Machine Learning with Scikit-Learn, Keras, and TensorFlow” by Aurelien Geron.
- “Deep Learning” by Ian Goodfellow, Yoshua Bengio, and Aaron Courville
- “Artificial intelligence (AI): A Modern Approach” by Stuart Russell and Peter Norvig
We will be talking about different online courses that can be used to learn AI later in this article.
Some of the videos and tutorials that can be used to learn AI include YouTube channels like:
- PW Skills College Wallah
- 3Blue1Brown
- StatQuest
- MIT OpenCourseWare
4. Practice on Projects
Well, now we will be learning practically with the help of projects. Start with simple datasets and then eventually move towards real-world projects, including:
- Image Classification project
- Natural Language Processing (NLP) tasks (such as sentiment analysis)
- Predictive analytics with structured data
The projects can be done on platforms like Kaggle and Google Colab for practice.
5. Specialize in Subdomain
AI is a very fast field that consists of various domains, including NLP, GenAI, and many more. Now, choose the field that interests you. Some of the common fields are:
- Computer Vision: Image Processing, Object Detection, Gesture Detection, and many more
- Natural Language Processing (NLP): Chatbots, language models, and many more
- Reinforcement Learning: Game AI, robotics, and many more
- Generative AI: GANs, diffusion models, and many more.
6. Engage with the Community
Join different forums and communities to get the latest insights and news about the technology and its latest updates. Contribute to open-source projects on GitHub. Some of the discussions and forums can be found as:
- Kaggle Discussions
- Reddit’s r/MachineLearning
- AI/ML meetups
7. Build a Portfolio
Showcase your projects on GitHub or personal blogs. Create a LinkedIn profile highlighting your AI skills. Write articles or tutorials to demonstrate your expertise.
Be consistent, and hands-on practice is essential. Start small, be curious, and gradually take on bigger challenges!
How to Learn AI Course Online?
Learning AI is like embarking on a treasure hunt. The path will challenge you, but it is also full of discovery and rewards. Remember, the goal is not just to learn AI but to use it to create solutions that matter, whether it is improving lives, advancing industries, or simply satisfying your curiosity. Keep learning, keep experimenting, and enjoy the ride!
The best course depends upon the learner’s goals, background, and level of expertise. Some of the courses have been curated according to different categories.
For Beginners: Generative AI Bootcamp with PW Skills
This course offers complete tutorials for Generative AI and interactive frameworks. Get industry led live sessions with industry oriented curriculum. The course duration is 6 months with candidates having knowledge of AI Fundamentals, AI ethics, and AI tools.
Learn machine learning algorithms, deep learning techniques and more with Generative AI Course.
For Beginners: Start Your AI Journey: Machine Learning by Andrew Ng (Coursera)
This course offers a foundational understanding of machine learning as it covers algorithms like linear regression, logistic regression, and neural networks. It simplifies complex topics with clear explanations.
This course is about 11 weeks and needs to have some prerequisites related to basic math and programming. It is available on Coursera.
For Hands-On Deep Learning: Deep Learning Specialization by Andrew Ng (Coursera)
This course focuses on neural networks, CNNs, RNNs, and more. Also, it includes practical coding exercises using TensorFlow and Python. This course is taught by one of the most respected names in AI.
This course consists of 5 different courses that take about 3-4 months to complete. This course just requires familiarity with Python and Machine Learning basics.
For Practical, Code-First Learning: Practical Deep Learning for Coders by Fast.ai
This course focuses on building AI models with minimal theory upfront. Also, this course encourages hands-on learning using PyTorch. Ideal for those who want to build projects quickly.
This is a self-paced course and is free of cost. It takes about 8 weeks to complete with some programming experience.
For Comprehensive AI Understanding: AI for Everyone by Andrew Ng (Coursera)
This course gives a non-technical overview of AI for business and societal impact. It is designed for leaders, managers, or anyone curious about AI.
The course is about 4 weeks and has no prerequisites. The course is available at Coursera.
For Advanced Topics in AI: CS50’s Introduction to Artificial Intelligence with Python (edX)
This course covers search algorithms, knowledge representation, machine learning, and NLP. This course includes practical projects like handwriting recognition and game-playing agents. This course is taught by Harvard faculty.
The course is about 12 weeks long, and one should have basic Python programming knowledge. This course is available on EdX for, except the certificate.
Learn AI FAQ
Q1. Can you learn AI if you are a beginner?
Ans. Yes, you can learn AI if you are a beginner. There is a step-by-step procedure to learn AI as a beginner. A detailed analysis about how to learn AI is mentioned above in the article.
Q2. How do I start learning AI?
Ans. Learning Artificial Intelligence (AI) is a step-by-step procedure to upskill yourself in the fields of automation, neural networks, and many more. Learning AI can be a rewarding and exciting journey. So the basic steps included in learning AI are mentioned above in the article.
Q3. How long does it take to learn AI?
Ans. There are different courses, and according to these courses, the timing varies. There are several courses mentioned above in the article.
