Artificial intelligence and Machine learning course
Learn Artificial intelligence (AI) and train computer, human intelligence processes through application of algorithms
Updated on Jan, 2026
Language - English
IT and Software ,Other IT and Software,
Lectures -8
Duration -2 hours
Lifetime Access
Lifetime Access
30-days Money-Back Guarantee
Get your team access to 10000+ top Tutorials Point courses anytime, anywhere.
Course Description
Artificial intelligence (AI) is the basis for mimicking human intelligence processes through the creation and application of algorithms built into a dynamic computing environment. Stated simply, AI is trying to make computers think and act like humans.
Achieving this end requires three key components:
Why is artificial intelligence important?
Today, the amount of data that is generated, by both humans and machines, far outpaces humans’ ability to absorb, interpret, and make complex decisions based on that data. Artificial intelligence forms the basis for all computer learning and is the future of all complex decision making. As an example, most humans can figure out how to not lose at tic-tac-toe (noughts and crosses), even though there are 255,168 unique moves, of which 46,080 end in a draw. Far fewer folks would be considered grand champions of checkers, with more than 500 x 1018, or 500 quintillion, different potential moves. Computers are extremely efficient at calculating these combinations and permutations to arrive at the best decision. AI (and its logical evolution of machine learning) and deep learning are the foundational future of business decision making.
Applications of AI can be seen in everyday scenarios such as financial services fraud detection, retail purchase predictions, and online customer support interactions. Here are just a few examples:
Machine Learning is naturally a subset of AI. It provides the statistical methods and algorithms and enables the machines/computers to learn automatically from their previous experiences and data and allows the program to change its behavior accordingly.
Achieving this end requires three key components:
- Computational systems
- Data and data management
- Advanced AI algorithms (code)
Why is artificial intelligence important?
Today, the amount of data that is generated, by both humans and machines, far outpaces humans’ ability to absorb, interpret, and make complex decisions based on that data. Artificial intelligence forms the basis for all computer learning and is the future of all complex decision making. As an example, most humans can figure out how to not lose at tic-tac-toe (noughts and crosses), even though there are 255,168 unique moves, of which 46,080 end in a draw. Far fewer folks would be considered grand champions of checkers, with more than 500 x 1018, or 500 quintillion, different potential moves. Computers are extremely efficient at calculating these combinations and permutations to arrive at the best decision. AI (and its logical evolution of machine learning) and deep learning are the foundational future of business decision making.
Goals
Requirement of Artificial intelligenceApplications of AI can be seen in everyday scenarios such as financial services fraud detection, retail purchase predictions, and online customer support interactions. Here are just a few examples:
- Fraud detection. The financial services industry uses artificial intelligence in two ways. Initial scoring of applications for credit uses AI to understand creditworthiness. More advanced AI engines are employed to monitor and detect fraudulent payment card transactions in real time.
- Virtual customer assistance (VCA). Call centers use VCA to predict and respond to customer inquiries outside of human interaction. Voice recognition, coupled with simulated human dialog, is the first point of interaction in a customer service inquiry. Higher-level inquiries are redirected to a human.
- When a person initiates dialog on a webpage via chat (chatbot), the person is often interacting with a computer running specialized AI. If the chatbot can’t interpret or address the question, a human intervenes to communicate directly with the person. These noninterpretive instances are fed into a machine-learning computation system to improve the AI application for future interactions.
Machine Learning is naturally a subset of AI. It provides the statistical methods and algorithms and enables the machines/computers to learn automatically from their previous experiences and data and allows the program to change its behavior accordingly.
Prerequisites
To learn AI, you should first have a basic understanding of mathematics, especially linear algebra, probability, statistics, and simple calculus. Python programming is essential, along with familiarity with libraries like NumPy, Pandas, and Scikit-Learn. You should also know how to handle and clean data, visualize it, and understand core machine learning concepts such as supervised and unsupervised learning, regression, classification, and model evaluation. For advanced AI, learning neural networks and deep learning frameworks like TensorFlow or PyTorch is helpful. Basic computer science concepts and strong analytical thinking further strengthen your foundation for mastering AI.
Curriculum
Check out the detailed breakdown of what’s inside the course
Artificial Intelligence & Machine Learning
8 Lectures
-
AI ML introduction to machine learning
11:09
11:09
-
AI ML exploring python pandas uploading flat file data and perform operations
31:21
31:21
-
AI ML usage of pandas numpy and matplotlib for exploring numerical data
14:07
14:07
-
Ai ml understanding linear regression
23:20
23:20
-
Ai ml understanding logistic regression
04:57
04:57
-
Ai ml principal component analysis pca and k means clustering
21:44
21:44
-
Ai ml deep dive into neural networks
13:06
13:06
-
Ai ml retrain data to create classifier using google inception model
07:11
07:11
Instructor Details
Amit Kumar
Amit Kumar is a skilled and approachable instructor who loves sharing practical knowledge with his learners. With strong hands-on experience in his field, he focuses on teaching concepts in a clear and easy-to-understand way. Amit believes in simplifying complex topics and guiding students with real examples, making learning more engaging and useful. His friendly teaching style and commitment to student success make him a trusted mentor for learners at all levels.
Course Certificate
Use your certificate to make a career change or to advance in your current career.
Our students work
with the Best
Related Video Courses
View MoreAnnual Membership
Become a valued member of Tutorials Point and enjoy unlimited access to our vast library of top-rated Video Courses
Subscribe now
Online Certifications
Master prominent technologies at full length and become a valued certified professional.
Explore Now