Free AI with Python Course

Artificial Intelligence with Python

Learn Artificial Intelligence with Python from basics in this free online training. This free AI with Python course is taught hands-on by experts. Learn about neural networks, Perceptron, Loss Function. Best for Beginners.

Instructor:

Prof. Mukesh Rao
4.54
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Intermediate

Level

11.25 Hrs

Learning hours

74.2K+
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Artificial Intelligence with Python

11.25 Learning Hours . Intermediate

Skills you’ll Learn

About this course

Take a free course on Artificial Intelligence with Python and learn the fundamentals of AI. Learn how to use Python to create intelligent systems, explore machine learning algorithms, and apply AI techniques to real-world problems. 

 

This course will introduce you to Python programming for Artificial Intelligence, with a few demonstrated samples.  It shall begin with comprehending the history of Neural Networks. It shall imbibe in you the knowledge of the difference between a biological neuron and an artificial neuron, Perceptron and working mechanism, architecture of ANN, different functions such as activation, softmax, its forward propagation, and loss as you follow the first half of the course. The second part engages you by demonstrating tasks using the Keras framework, propagation and gradient descent, and an application study on the MNIST data set. You will also understand the working of Tensorflow 2.0 in the course. Take up the quiz at the end of the course to test your skills and evaluate your gains to avail of the certificate.

 

After this free, self-paced, intermediate’s guide to Artificial Intelligence with Python, you can enroll in the Artificial Intelligence courses and embark on your career with the professional Post Graduate certificate and learn different concepts in depth with millions of aspirants worldwide!

 

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Course Outline

History behind neural networks

This module will introduce you to the history of neural networks, the early experiments, limitations, and how ANN evolved to build almost every technology that is in use today. 
 

Relationship between biological neuron and artificial neuron

You will understand the supervised learning technique, ANN, and learn how it differs from the biological neural system. In this section, you will also learn why artificial neural networks are dependent on biological neurons to perform a few crucial tasks, along with understanding dense neural networks. 
 

Perceptron and working mechanism

You will understand the mathematical model of biological neurons in this module. As you follow this module, you will also understand how an artificial neuron mimics the biological neuron and the mechanism to do so. 
 

Architecture of artificial neural network

You will understand different elements in artificial neural networks, different layers, and their functionalities in this section. The section briefly discusses how each layer contributes to processing the data to produce accurate output. 
 

Types of activation functions

At the beginning of this section, you will understand what classification is and why it is performed in ANN. You will then understand regression, ANN with respect to Perceptron, and the functions that make the building blocks of ANN as you follow the module. 
 

Softmax function

You will understand the softmax function with multi-class classification in deep neural networks. You will learn the working mechanism of the softmax function with an example as you follow this section. 
 

Forward propagation

This section discusses how the entire data set passes through the different layers of the neural network. You will understand forward propagation and its mechanism with matrix operation, how the process results in the error, and also understand the mechanism to fix this error. 
 

Loss function

This section explains what error functions are, their properties, and the mathematics behind them with an example to help you understand what mean least loss is. 
 

Demo using keras framework

You will understand what Keras is, its elements, features, and working in this section. You will also learn to work with Keras, an interface for Tensorflow, to reduce the cognitive load of ANN with demonstrated programming. 
 

Back propagation and gradient descent

You will understand how an error is resolved using back propagation at the beginning of this section. Later, you will learn about vanishing gradients and exploding gradients concepts and their mathematical functioning to understand gradient descent. 
 

Tensorflow 2.0

You will understand what Tensorflow is and why Keras is used for Tensorflow. You will learn about the tensors, features of the Tensorflow 2.0 version, syntax, and how all machine learning processes can be performed using Tensorflow.
 

Demo on MNIST data set

You will learn to work with the discussed concepts in the Jupyter notebook with the MNIST dataset in this section. 
 

Our course instructor

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Prof. Mukesh Rao

Director, Academics, Great Learning

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118.4K+ Learners
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8 Courses
Prof. Mukesh Rao is a senior faculty of Data Science in Great Learning and he is responsible for designing data science courses offered and mentoring students with capstone projects. Prof. Mukesh has over 20 years of industry experience in Market Research, Project Management, and Data Science and has conducted extensive corporate training in Data Science and Big Data. He also works as a Data Science Trainer & Consultant for 4v Technologies and conducts training in core big data technologies and data science. He has headed Big Data teams at SourceOne and has worked with tech giants like Wipro Technologies.

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What our learners say about the course

Find out how our platform helped our learners to upskill in their career.

4.54
Course Rating
73%
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What our learners enjoyed the most

Ratings & Reviews of this Course

Reviewer Profile

5.0

Gained Hands-On Experience in Building AI Models Using Python and Exploring Real-World Applications
I enjoyed the practical approach of the course, especially the hands-on projects that allowed me to implement various AI algorithms. The Python-based exercises, combined with clear explanations of complex concepts like neural networks and natural language processing, made learning engaging and rewarding. The support from instructors and detailed coding examples were also fantastic for grasping difficult topics.
Reviewer Profile

5.0

My Fun Learning Journey in Great Learning
I really enjoyed the quizzes and assignments. They helped me understand the topics better and made learning fun! The instructor was great and explained things simply, which made everything clear. I also liked the tools we used. They were very helpful!
Reviewer Profile

5.0

Gained More Knowledge by Learning Artificial Intelligence with Python
I gained more knowledge through this session. It was very interesting and easy to understand.
Reviewer Profile

5.0

I Am Very Happy After Completing This Course. It Helped Me Enhance My Skills in Artificial Intelligence
The instructor's method of teaching is awesome. The material or topics covered in this course were also advanced and great. I enjoyed the learning very much.
Reviewer Profile

5.0

AI Course Feedback: A Comprehensive Learning Experience
This AI course provided a solid foundation in the field, covering key concepts and practical applications. The curriculum was well-structured, and the instructors were knowledgeable and engaging. The interactive quizzes and assignments were helpful for reinforcing learning. The course also provided valuable insights into real-world AI applications. Overall, it was a great learning experience.
Reviewer Profile

4.0

The Course Was Really Interactive and Helped Me Understand More About Deep Neural Networks
The instructor was really nice and took time to explain everything in this course. His attention to detail is what made me keep interest in this course rather than shelve it in a dark corner.
Reviewer Profile

5.0

Enjoyed Learning New Things in Just a Day. Happy to Have Found This Course
Extremely happy and motivated to learn from such a platform.
Reviewer Profile

5.0

Artificial Intelligence and Neural Networks
An in-depth understanding of neural networks and how they work! Learned a lot about machine learning and practical applications of deep neural networks in real life. A very fascinating topic, and classes were easy to follow.
Reviewer Profile

5.0

Mastering AI: A Comprehensive Guide to Machine Learning Concepts and Applications
Your work on mastering AI through machine learning is impressive! The comprehensive approach to concepts and applications demonstrates a solid understanding of the subject. However, adding more real-world case studies and practical examples could enhance the learning experience. Keep up the great effort, and continue exploring cutting-edge trends in AI to further expand your knowledge.
Reviewer Profile

5.0

Learning Made Easy with Great Resource Sharing
Very simple to follow and straightforward comprehension of the courses.

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Artificial Intelligence with Python

11.25 Learning Hours . Intermediate

Frequently Asked Questions

What are the prerequisites required to learn the Artificial Intelligence with Python course?

Artificial Intelligence with Python is an intermediate-level course, and you can begin the course with good knowledge of computer science. You will also have to do a little homework to boost your learning, so we suggest you learn the basics of Deep Learning and Neural Networks before starting this course.

Will I have lifetime access to this free course?

Yes, once you enroll, you will have lifetime access to this Great Learning Academy's free course. You can log in and learn at your leisure.

What are my next learning options after this Artificial Intelligence with Python course?

Once you complete this free course, you can opt for a PG Program in Artificial Intelligence that will help advance your career growth in this leading field.

 

Is it worth learning Artificial Intelligence with Python?

Yes, it is beneficial to learn Artificial Intelligence with Python. Artificial Intelligence being one of the leading technologies in the world today, the market for AI and ML professionals only grows every day. If you are thorough with Python programming, then it serves as a one-stop to carry out all the tasks in Keras and Tensorflow. 

 

 

What is Artificial Intelligence with Python used for?

Python programming language has libraries and packages that make it straightforward and more accessible for the programmers to work on machine learning tasks. You can also work with Keras and Tensorflow to automate processes to help the artificial neurons process the data and result in accurate outputs. 

 

Why are Artificial Intelligence and Python so popular?

Artificial intelligence is a technology that mimics human intelligence to reduce manual work for repetitive and decision-making tasks. On the other hand, Python programming is a user-friendly language that comprises several in-built libraries to make coding easier.

Why are Artificial Intelligence and Python so popular?

Artificial intelligence is a technology that mimics human intelligence to reduce manual work for repetitive and decision-making tasks. On the other hand, Python programming is a user-friendly language that comprises several in-built libraries to make coding easier.

Will I get a certificate after completing this free Artificial Intelligence with Python course?

Yes, you will get a certificate of completion for this course after completing all the modules and cracking the quiz/assessment. The assessment tests your knowledge of both Artificial Intelligence and Python and badges your skills. 

 

What knowledge and skills will I gain upon completing this course?

You will gain the foundational knowledge of how to use Python Programming for Artificial Intelligence and Machine Learning tasks through this course. Upon completing Artificial Intelligence with Python, you will get familiar with ANN, its working mechanism, functions, Keras, and Tensorflow.

How much does this Artificial Intelligence with Python course cost?

It is an entirely free course from Great Learning Academy. Anyone interested in learning ANN, Keras, and Tensorflow and understanding the mechanism behind it can get started with this course.

Is there any limit on how many times I can take this free course?

Once you enroll in this free Artificial Intelligence with Python course, you will have lifetime access to it. So, you can log in to the course anytime and learn it online at your leisure.

Can I sign up for multiple courses from Great Learning Academy at the same time?

Yes, you can enroll in as many courses as you want from Great Learning Academy. There is no stricture to the number of courses you can enroll in at once. All the courses offered by Great Learning Academy are free, so we propound you learn one at a time to get the best out of the courses.

Why choose Great Learning Academy for this free Artificial Intelligence with Python course?

Great Learning is a global educational technology platform committed to developing skilled professionals. Great Learning Academy is a Great Learning project that provides free online courses to assist people in succeeding in their careers. Great Learning Academy's free courses have helped over 4 million students from 140 countries. It's a one-stop destination for all of a student's needs.

 

This course is not only free and self-paced, but it also includes solved problems, demonstrated codes, and presented examples to help you comprehend the numerous areas that fall under the subject. The course is conducted by topic experts and is carefully tailored to cater to both beginners and professionals.

 

Who is eligible to take this course?

Anybody with basic knowledge of computer science, probability, calculus and a good hold on Python Programming, interested in learning ANN, Keras, and Tensorflow and understanding their working mechanism can take up the course. So, enroll in our AI with Python today and learn it for free online.

What are the steps to enroll in this Artificial Intelligence with Python course?

Enrolling in Great Learning Academy's AI with Python is a simple and straightforward approach. You will have to sign-up with your E-Mail ID, enter your user details, and then you can start learning at your own pace.

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