infyni

Live Artificial Intelligence For Beginners Course

Discover the fundamentals of Artificial Intelligence with our Live AI for Beginners Course. Perfect for novices, this course navigates through AI concepts, machine learning basics, and practical applications, guided by industry experts in an interactive learning environment.

Live Course

Live Class: Monday, 22 Jan

Duration: 25 Hours

Enrolled: 0

Offered by: infyni

Live Course

About Course

Engaging journey into the world of Artificial Intelligence (AI) with our Live Course for Beginners. This comprehensive course offers an introduction to AI, covering foundational concepts, machine learning basics, AI applications, and ethical considerations.

Led by industry experts, these interactive sessions aim to demystify AI, providing insights into its principles, techniques, and real-world applications.

This course aims to introduce beginners to the world of Artificial Intelligence, covering fundamental concepts, machine learning basics, AI applications, and ethical considerations.

Through interactive sessions led by industry experts, participants will gain insights into the principles and practical applications of AI, setting the foundation for further exploration in this rapidly evolving field.

Skills You Will Gain

AI Fundamentals Machine Learning Basics AI Algorithms and Models Data Preprocessing and Feature Engineering AI Applications and Use Cases Ethical Considerations in AI AI Tools and Frameworks

Course Offerings

Instructor-led interactive classes
Clarify your doubts during class
Access recordings of the class
Attend on mobile or tablet
Live projects to practice
Case studies to learn from
Lifetime mentorship support
Industry specific curriculum
Certificate of completion
Employability opportunity

Topics
Instructor (1)

1 Introduction to AI/ML

AI/ML Applications
Motivation
Classification
Regression

2 Python Basics

Python Compiler
Variables
Basic Arithmetic
Lists

3 Neural Networks Basics

A Single Neuron

4 Fully Connected networks (FCN)

Multi layer neural networks

5 Basic of Keras + FCN Coding

Coding a single layer neural network with keras essentials
Coding a multiple layer neural network with keras amenities

6 Project - FCN Application

Using keras for FCN on MNIST data

7 Convolutional Neural Network (CNN)

Basics of convolutional, pooling and activation layers
CNN Architectures

8 Keras introduction for CNN

Coding of CNN using keras

9 Project - CNN Applications

Coding of CNN using keras

10 Recurrent Neural Network (RNN)

Limitation of CNN and Introduction to RNN
Details of RNN

11 Time series forecasting using RNN

Daksh Thapar

About Instructor

I am Daksh Thapar, a Ph.D. student at the Indian Institute of Technology Mandi (IIT Mandi), India. My main area of research is analyzing different behavioral biometrics from videos. I am fluent in state-of-the-art deep learning technologies and also in tensorflow and PyTorch. Apart from behavioral biometrics, I have also worked on Bioacoustics, bio-imaging, physiological biometrics, and medical imaging. I have published multiple papers in top conferences and journals.

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