How to Learn AI in 2024
Have you ever wondered how machines can learn to recognize images, translate languages, or even beat world champions at complex board games? If so, then you're already on your way to understanding the basics of artificial intelligence. AI is a rapidly growing field that has the potential to revolutionize the way we live and work. From autonomous vehicles to virtual assistants, AI is already playing a significant role in our daily lives, and the demand for skilled AI professionals is only going to increase in the coming years. But where should you start if you want to learn AI in 2024? With so many resources available, it can be overwhelming to know where to begin. In this article, we will provide a step-by-step guide on how to acquire the skills, knowledge, and experience necessary to succeed in the exciting and rapidly growing field of AI.
Table of Contents
- What is Artificial Intelligence?
- Why Learn Artificial Intelligence?
- How to Learn Artificial Intelligence: A Complete Roadmap
- From Where to Learn Artificial Intelligence: Top Degree Courses and Certificates
What is Artificial Intelligence?
Artificial Intelligence (AI) is a field of computer science that enables machines to perform tasks that normally require human intelligence, such as recognizing speech, understanding language, making decisions, and solving problems.
In other words, AI is the ability of machines to think and learn like humans, making them capable of performing tasks that would otherwise require human intervention.
Types of Artificial Intelligence
- Machine Learning (ML): Machine learning is a subset of AI that focuses on building systems that can learn from and make decisions based on data. ML models adjust their parameters on their own to improve their accuracy over time, typically without human intervention. There are three main types of machine learning:
- Supervised Learning: Models are trained on labelled data (data that has been categorized or tagged with the correct answer).
- Unsupervised Learning: Models infer patterns from unlabeled data without reference to known or labelled outcomes.
- Reinforcement Learning: Models learn to make sequences of decisions by receiving feedback in the form of rewards or punishments.
- Deep Learning: Deep learning is a subset of machine learning that uses neural networks with three or more layers. These neural networks attempt to simulate the behavior of the human brain—albeit far from matching its ability—to process data and create patterns for use in decision making. Deep learning is particularly powerful for handling large amounts of unstructured data such as images and video.
- Neural Networks: Neural networks are a class of models within deep learning designed to recognize patterns. They interpret sensory data through a kind of machine perception, labeling, or clustering. The architecture of a neural network resembles the network of neurons in the human brain, consisting of layers of interconnected nodes (neurons). Each connection, like the synapses in a biological brain, can transmit a signal from one artificial neuron to another. The neural network's task is to adjust the strength of the connections (weights) between nodes, which is done during training.
- Cognitive Computing: Cognitive computing models aim to simulate human thought processes in a computerized model. Using self-learning algorithms that use data mining, pattern recognition, and natural language processing, these systems can mimic the way the human brain works.
- Computer Vision: This field involves enabling computers to see, identify and process images in the same way that human vision does, and then provide appropriate output. It is closely related to artificial neural networks, as neural networks are often used to power image recognition capabilities.
Best-suited Machine Learning courses for you
Learn Machine Learning with these high-rated online courses
Why Learn Artificial Intelligence?
- High demand for AI talent: According to the World Economic Forum, AI-related job roles have grown by 74% annually in recent years, indicating a high demand for AI talent.
- Higher Salaries: According to data from AmbitionBox.com, AI engineers are among the highest-paid software engineers, with an average salary of INR 11.2 Lacs per year in India.
- Career Opportunities: With AI being integrated into various industries, such as healthcare, finance, and transportation, there are ample career opportunities for those with AI skills.
- Machine Learning Engineer: This role combines software engineering with data science to build and deploy machine learning models. These models can be used for tasks like image recognition or making sales predictions.
- Data Scientist: Data scientists analyze large datasets to extract insights and knowledge. They often play a crucial role in preparing data for machine learning models.
- Research Scientist: AI research scientists are at the forefront of the field, pushing the boundaries of what AI can do. They may work on developing new algorithms or applications for AI.
- AI Engineer: A broad role that can encompass various tasks related to designing, developing, and implementing AI systems.
- NLP Engineer: Specializes in Natural Language Processing (NLP), which allows machines to understand and process human language. NLP engineers work on applications like chatbots or voice assistants.
- Robotics Scientist: Develops and improves robots, often incorporating AI for tasks like navigation or decision-making.
- Big Data Engineer: Creates and maintains the infrastructure required to store and process the massive datasets that AI systems rely on.
- Business Intelligence Developer: Develops AI-powered tools and applications to help businesses gather and analyze data for better decision-making.
- Innovation: AI is a rapidly evolving field, with new breakthroughs and advancements being made every day. By learning AI, you can be part of the innovation and contribute to solving complex problems.
- Future-Proofing your Career: As AI automation continues to replace certain jobs, acquiring AI skills can future-proof your career and make you more employable in the years to come.
- Personal Development: Learning AI can be a challenging yet rewarding experience, providing opportunities for personal growth and development.
How to Learn Artificial Intelligence: A Complete Roadmap
Month |
Module |
Focus |
Resources |
1-2 |
Introduction to Programming |
Python programming basics, syntax, control structures |
Codecademy, Python.org tutorials |
1-2 |
Essential Mathematics |
Basics of linear algebra, calculus, statistics |
Khan Academy, Coursera courses |
3-4 |
Basics of Artificial Intelligence |
Understanding AI, history, applications, ethics |
AI For Everyone by Andrew Ng on Coursera |
3-4 |
Introduction to Machine Learning |
Supervised vs. unsupervised learning, basic algorithms |
Machine Learning by Andrew Ng on Coursera |
5-6 |
Deep Dive into ML Algorithms |
Decision trees, SVMs, ensemble methods |
Hands-On Machine Learning with Scikit-Learn and TensorFlow |
5-6 |
Data Preprocessing and Visualization |
Data cleaning, normalization, visualization |
Pandas and Matplotlib documentation, DataCamp courses |
7-8 |
Foundations of Neural Networks |
Neural network architecture, activation functions, backpropagation |
Deep Learning Specialization by Deeplearning.ai on Coursera |
7-8 |
Advanced Deep Learning Concepts |
CNNs, RNNs, LSTMs, and applications |
CS231n: Convolutional Neural Networks for Visual Recognition |
9-10 |
Choosing a Specialization |
NLP, Computer Vision, Robotics, etc. |
Specialized courses on Coursera and other platforms |
9-10 |
Practical AI Projects |
Applying AI to real-world problems |
GitHub, Kaggle competitions |
11-12 |
Advanced AI Topics |
Reinforcement learning, generative models, advanced techniques |
Advanced Machine Learning Specialization on Coursera, arXiv.org |
11-12 |
AI in Industry and Career Networking |
AI applications in business, career preparation, networking |
LinkedIn, local AI meetups, industry conferences |
From Where to Learn Artificial Intelligence: Top Online Degree, Diploma and Certificate Courses
Top Online Degree Programs in AI
No. |
Institution |
Program |
USP |
Course Fees |
Duration |
1 |
IIIT Hyderabad |
M.Tech in Artificial Intelligence |
Focus on research and real-world projects |
INR 3,00,000 |
2 years |
2 |
Amity University Online |
Designed for working professionals |
INR 1,50,000 |
3 years |
|
3 |
NMIMS |
MBA in Artificial Intelligence |
Blend of business and AI skills |
INR 2,40,000 |
2 years |
4 |
Great Lakes International University |
PGP in Artificial Intelligence and Machine Learning |
Collaboration with University of Texas at Austin |
INR 3,00,000 |
1 year |
5 |
Simplilearn in collaboration with Purdue University |
Post Graduate Program in AI and Machine Learning |
Practical learning with Purdue’s faculty |
INR 2,25,000 |
1 year |
6 |
Manipal Academy of Higher Education Online |
Flexible learning schedule |
INR 1,50,000 |
2 years |
|
7 |
BITS Pilani |
PG Program in AI and ML |
Offers workshops and live sessions |
INR 2,50,000 |
11 months |
8 |
Learning Paths School (LPS) |
Masters in AI and Machine Learning |
Project-based learning, flexible hours |
INR 3,00,000 |
2 years |
Top Online Diploma and Certificate Courses in AI
No. |
Provider |
Program |
USP |
Course Fees |
Duration |
1 |
upGrad |
Partnership with IIIT Bangalore, job placement support |
INR 2,85,000 |
12 months |
|
2 |
Simplilearn |
Collaboration with Purdue University, IBM |
INR 2,25,000 |
12 months |
|
3 |
Great Learning |
Mentoring by industry experts, hands-on projects |
INR 3,00,000 |
12 months |
|
4 |
TalentEdge |
Advanced Certificate Program in AI & ML |
Executive learning from IIM faculty |
INR 1,20,000 |
5 months |
5 |
Coursera (offered through University of Colorado Boulder) |
Advanced Machine Learning Specialization |
Flexible schedule, globally recognized institution |
Varies with subscription |
4-6 months |
6 |
EdX (offered through Columbia University) |
Artificial Intelligence MicroMasters |
Comprehensive curriculum, pathway to a Master's degree |
INR 1,36,135 |
About 1 year |
7 |
Intellipaat |
AI & Deep Learning Course with TensorFlow |
24/7 learning assistance, job assistance |
INR 19,737 |
6 months |
8 |
Scaler Academy |
Data Science & Machine Learning Program |
Focus on competitive programming and machine learning |
INR 2,50,000 |
9 months |
9 |
Analytics Vidhya |
Certified AI & ML Blackbelt+ |
Community-driven learning platform |
INR 50,000 |
Self-paced |
10 |
NASSCOM |
AI Data Science and Big Data Analytics |
Government-supported, industry-recognized certification |
INR 25,000 |
4 months |
Vikram has a Postgraduate degree in Applied Mathematics, with a keen interest in Data Science and Machine Learning. He has experience of 2+ years in content creation in Mathematics, Statistics, Data Science, and Mac... Read Full Bio