Introduction to Artificial Intelligence and PythonIn Web Development
About this class
Artificial Intelligence has already transformed the way we live, work, and play, making it an indispensable part of our daily life. Al is required everywhere starting with the internet, online shopping, social networks, and continuing with recommendation systems by improving old ones like medical diagnostics and search engines. As a result, the demand for AI expertise is rapidly increasing, and we must understand how these technologies work. This course will help you take the first step toward solving important real-world problems and securing your career’s future. You’ll learn about the fundamental concepts of artificial intelligence and explore the concepts and algorithms that underpin modern AI with Python, delving into the concepts that underlies technologies like game-playing engines, and handwriting recognition. In this course you will study about the theory behind graph search algorithms, classification, optimization, reinforcement learning, and other artificial intelligence topics through hands-on projects that they incorporate into their own Python programs. This course could serve as a stepping stone toward a career in artificial intelligence. Enroll now with the leaders in science, We Speak Science University, to gain expertise in one of the fastest-growing domains of computer science. You will be able to freely communicate on topics related to Artificial Intelligence and neural networks after completing this course.
At the end of this course, you should be able to:
- 1.Analyze and visualize data, as well as applied algorithms to various problems.
- 2.Do graph search algorithms.
- 3.Recognize the principles of artificial intelligence.
- 4.Create systems that are intelligent.
- 5.In Python programs, to use artificial intelligence (AI).
- 6.Understand the fundamentals of the Python programming language, including basic syntax, variables, and types.
- 7.Create and Manipulate regular Python lists.
- 8.Import packages and use functions.
- 9.Create Numpy arrays and use them to perform complex calculations.
- 10.Create and personalize plots based on real-world data.
- 11.Use control flow in your scripts and the Pandas DataFrame.
- 1.Course Introduction
- 2.Introduction to Functions, Methods and Objects
- 3.Boolean Logic, Pandas and Data Visualization
- 4.History behind neural networks
- 5.Relationship between biological neuron and artificial neuron
- 6.Perceptron and working mechanism
- 7.Architecture of artificial neural network
- 8.Types of activation functions
- 9.Softmax function
- 10.Forward propagation
- 11.Loss function
- 12.Demo using keras framework
- 13.Back propagation and gradient descent
- 14.Tensorflow 2.0
- 15.Demo on MNIST data set