What is Artificial Intelligence?
Artificial intelligence is a branch of computer science that deals with building machines capable of performing complex tasks without human intervention. It combines data science with real-life data to leverage machines and computers to imitate the decision-making and problem-solving capabilities that the human mind has.
Authors Stuart Russell and Peter Norvig, in their groundbreaking book, Artificial Intelligence: A Modern Approach, discussed and explored four different approaches that historically defined the field of Artificial Intelligence.
- Thinking humanly
- Thinking rationally
- Acting humanly
- Acting rationally
Artificial Intelligence Courses
Artificial Intelligence is one of the fastest-growing fields in the Computer Science industry. Every student nowadays wants to enhance their artificial intelligence skills, as it has shown to be highly beneficial in improving their placement prospects.
Here are some Artificial Intelligence courses that you can pursue.
| Course | Type of Course | Institution / Organisation |
| Advanced Certification in Data Science and AI by IIT Madras | Training and Certification | IIT Madras, through Intellipaat |
| B.Tech / B.E. (CSE) with Specialization in Artificial Intelligence | Bachelor’s Degree | IIIT, Delhi |
| B.Tech (CSE) with Artificial Intelligence and Machine Learning | Bachelor’s Degree | Manipal Institute of Technology |
| B.Sc. Artificial Intelligence and Machine Learning | Bachelor’s Degree | Chandigarh Group of Colleges |
| PG Certification in Data Science and Machine Learning – MNIT | PG Certification | MNIT Jaipur through Intellipaat (In collaboration with IBM and Microsoft) |
| PG Diploma in AI | PG Diploma | CDAC (Centre for Development of Advanced Computing) |
| PG Diploma in Computer Science and Artificial Intelligence | PG Diploma | IIIT, Delhi |
| PG Diploma in Machine Learning and Artificial Intelligence | PG Diploma | IIIT, Bangalore |
| AI and ML PG Certification Programme | PG Certificate | BITS Pilani |
| Masters Course in Artificial Intelligence | Master’s Course | Intellipaat in collaboration with IBM |
| MSc in Data Science and Machine Learning | Master’s Degree | Reva University |
Other than these courses mentioned above, many BTech and MTech courses offered in Computer Science also combine many Artificial Intelligence related subjects in their curriculum.
Now that you have seen what the different courses in Artificial Intelligence are, let’s learn about the common subjects in the Artificial Intelligence Course Syllabus for these courses.
Topics and Subjects in Artificial Intelligence Course Syllabus
The Artificial Intelligence courses that we discussed are offered in various streams, countries and institutes. The exact syllabus will always differ, based on the course you’re pursuing and the college or university you’re studying in, but each one of these courses focuses on the same common subjects.
These subjects are designed in a way that they give an overview of Artificial Intelligence. Some of these and topics are-
All these subjects are usually included in every artificial intelligence course syllabus, be it any level of education from any university or country.
Most of these courses also include mandatory internships and live projects, during the course. These help the students to learn and understand better and get a better grasp of the subjects being taught.
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Artificial Intelligence Course Syllabus: Certification
To understand the A.I Course Syllabus for Specialization Certifications, let’s look at the syllabus of the Advanced Certification in Data Science and AI by IIT Madras offered by Intellipaat.
- Module 1 – Preparatory Sessions – Python & Linux
- Module 2 – GIT
- Module 3 – Python with Data Science
- Module 4 – Advanced Statistics
- Module 5 – Machine Learning & Prediction Algorithms
- Module 6 – Data Science at Scale with PySpark
- Module 7 – AI & Deep Learning using TensorFlow
- Module 8 – Deploying Machine Learning Models on Cloud (MLOps)
- Module 9 – Data Visualization with Tableau
- Module 10 – Data Science Capstone Project
- Module 11 – Data Analysis with MS Excel
- Module 12 – Data Wrangling with SQL
- Module 13 – Natural Language Processing and its Applications
The cost of such trainings and certifications can vary, depending on the course, the offering body, and the quality of the training and the experience of the faculty.
Next, let’s discuss the undergraduate courses.
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Machine Learning Course Syllabus: Undergraduate
UG Certification in Machine Learning Course Syllabus
After looking at the course syllabi of some UG certifications in machine learning, we could conclude that the machine learning course syllabus for any UG certification usually follows the same pattern. Let’s understand that.
- Foundation
- Machine Learning
- Featurization, Model Selection & Tuning
- Artificial Intelligence
- Introduction to Neural Networks and Deep Learning
- Natural Language Processing
- Additional Modules
- Pre Work for Deep Learning
- Visualization using a Tensor board
- GANs (Generative Adversarial Networks)
These courses are usually offered in online mode by many reputed colleges, universities and organizations, including highly prestigious IITs like IIT Madras.
Bachelor’s Degree in Artificial Intelligence Course Syllabus
You can pursue a Bachelor’s degree in either a 6-semester-long course like Computer Science, or an 8-semester-long course in Engineering or Technology, with specialization in Artificial Intelligence.
| Semester 1 | Semester 2 |
| Object Oriented Programming With C++ | Soft Skills |
| English Language and Communication Skills | Programming in JAVA |
| Data Structures and Algorithms | Basic Internet Laboratory |
| Discrete Mathematics | Applied Mathematics |
| Environmental Studies | Human Resources and Rights |
| Semester 3 | Semester 4 |
| Programming in Python | AI and Knowledge Representation |
| Fuzzy Logic and Neural Networks | Introduction to Machine Learning |
| Design and Analysis of Algorithms | Programming in R |
| Introduction to Internet of Things | Skill Based Project Work |
| Language Elective | Major Elective |
| Semester 5 | Semester 6 |
| Machine Learning Techniques | Embedded Systems |
| Ethical Hacking | Natural Language Processing |
| Deep Learning | Artificial Neural Networks |
| Data Analytics Techniques | Machine Learning Live Project |
If you’re pursuing an 8-semester-long course, you might study some additional subjects like Human Computer Interaction, Pattern Recognition and Augmented Reality.
Artificial Intelligence Course Syllabus: Post-Graduate
Course Syllabus for PG Certification in Artificial Intelligence
Let’s look at the syllabus of the PG Certification in Artificial Intelligence offered by Intellipaat, to understand the Artificial Intelligence Course Syllabus for PG Certifications.
- Module 1 – Preparatory Classes on Python for AI & ML and Linux
- Module 2 – Git and GitHub
- Module 3 – Python with Data Science
- Module 4 – Data Wrangling with SQL
- Module 5 – Story Telling
- Module 6 – Machine Learning Models for Selection and Tuning
- Module 7 – Machine Learning & Prediction Algorithms
- Module 8 – Advanced Machine Learning
- Module 9 – Software Engineering for Data Science
- Module 10 – Data Science at Scale with PySpark
- Module 11 – Artificial Intelligence and Deep Learning with TensorFlow
- Module 12 – Natural Language Processing
- Module 13 – Image Processing and Computer Vision
- Module 14 – Deployment of Machine Learning Systems to Production
- Module 15 – Work with Large Datasets
- Module 16 – Data Visualization with Tableau
- Module 17 – Capstone Project
- Module 18 – Data Science with R
Program Content for Master’s Certification in Artificial Intelligence
To understand the syllabus for Master’s Certifications in Artificial Intelligence, let’s go through the curriculum of Intellipaat’s Masters in Artificial Intelligence Course.
- Data Science with R
- Python
- Machine Learning
- Artificial Intelligence & Deep Learning with TensorFlow
- Natural Language Processing
- Advanced Deep Learning and Computer Vision
- AWS Big Data
- SAS
- Advanced Excel
- Tableau Desktop 10
Subjects to be Explored in Master’s Degree in Artificial Intelligence
After completing your graduation, you are eligible to pursue a 2-year-long Master’s program in Artificial Intelligence. We analyzed the A.I Course Syllabus for Master’s Programs in various reputed universities and colleges around the world and concluded that the students usually have to study the following core and elective subjects.
- Core Subjects
- Ethics, Privacy, AI in Society
- Introduction to Machine Learning
- Introduction to Symbolic Artificial Intelligence
- M.Sc Software Engineering Practice and Group Project
- Python Programming
- Individual Project
- Elective Subjects
- Advanced Databases
- Advanced Robotics
- Advanced Security in Smartphone and IoT Systems
- Complexity
- Computational Finance
- Computer Vision
- Databases
- Deep Learning
- Knowledge Representation
- Logic-Based Learning
- Machine Arguing
- Machine Learning for Imaging
- Maths for Machine Learning
- Modal Logic
- Network and Web Security
- Operations Research
- Optimisation
- Performance Engineering
- Principles of Distributed Ledgers
- Privacy Engineering
- Probabilistic Inference
- Probabilistic Programming
- Prolog
- Quantum Computing
- Reinforcement Learning
- Robotics
- Scalable Systems for the Cloud
- Separation Logic: Local Reasoning about Programs
- Systems Verification
In the above section, we have seen what are the subjects in artificial intelligence that are really important in the AI domain. Now let us go through the best book recommendations for Artificial Intelligence Course Syllabus.
Book recommendations for Artificial Intelligence Course Syllabus
Bachelor’s Degree
Given below is a list of books that may be useful to the students pursuing a Bachelor’s Degree in Artificial Intelligence.
| Book | Author(s) |
| Data Structures | Ellis Horowitz, Sartaj Shani |
| Discrete Mathematics and its Applications | Kenneth H. Rosen |
| Python the Complete Reference | Martin C. Brown |
| Artificial Intelligence: A Systems Approach | S. Russell, P. Norvig |
| A Hundred page Machine Learning Book | Andriya Burkov |
| Neural Networks and Fuzzy Systems | Kosko |
| Machine Learning: The art and Science of Algorithms that make sense of Data | Peter Flach |
| Artificial Intelligence: A modern Approach | Stuart J. Russell and Peter Norwig |
Master’s Degree
The following books will be useful if you’re pursuing a Master’s Degree in Artificial Intelligence.
| Book | Author(s) |
| Deep Learning | Ian Goodfellow, Yoshua Bengio, Aaron Courville, Francis Bach |
| Python Machine Learning | Sebastian Raschka and Vahid Mirjalili |
| Pattern Recognition and Machine Learning | Christopher Bishop |
| The Elements of Statistical Learning | Trevor Hastie, Robert Tibshirani, Jerome Friedman |
| Speech and Language Processing | Daniel Jurafsky and James H. Martin |
Now that we’ve discussed various Artificial Intelligence Courses at different levels, as well as the syllabi that they cover, hopefully, you’re more familiar with the field of Artificial Intelligence and might be interested to pursue it.