preloder

Artificial Intelligence

Artificial Intelligence (AI) is a field that has immense potential and is evolving at lightning speed every day. We brings an introductory course on AI that teaches the history, basic terminology, and some of the representative applications of AI. It touches upon essential math and machine learning basics, with hands-on assignments that serve to reinforce learning. This workshop provides a stepping stone into the world of AI and is hence the perfect course for those wish to understand the huge possibilities in the field of AI, and how they could leverage it to enrich the capabilities of their businesses.

Artificial Intelligence has been predicted to be the most in-demand job in the coming years. According to IDC, the total spending on products and services that incorporate Augmented Reality and/or Virtual Reality concepts will soar from 11.4 billion as of 2017, to almost 215 billion by the year 2021. This is great news for AI career aspirants as the demand for such IT professionals will reach the sky in the coming years.

This course will help you learn the basics of modern AI as well as some of the representative applications of AI. You will get into the core fundamentals of AI and learn about programming concepts, including heuristic search and genetic programming, developing games and building intelligent applications that will be used to deliver solutions to problems in organizations and business. Along the way, we also hope to excite you about the numerous applications and huge possibilities in the field of AI, which continues to expand human capability beyond our imagination.

Skills you will learn

  • Machine Learning Techniques
  • Clustering
  • Natural Language Processing
  • Building Games
  • Build intelligent systems
  • Deep learning algorithms
  • Reinforcement Learning
  • Real-time Object Detection

Who should take this course?

  • Python developers who want to build real-world AI applications
  • Python beginners who want a comprehensive learning plan
  • Experienced programmers looking to use AI in their existing technology stacks

Foundation of AI

1
What is AI?
2
Python for AI
3
Probability
4
Visualization Techniques
5
Case Study

Supervised Learning

1
Regression (Linear, Multiple and Logistic)
2
Classification (K-NN, Naive Bayes) Techniques
3
Decision Trees
4
Case Study

Unsupervised Learning

1
K-means Clustering
2
Hierarchical Clustering
3
High-dimensional Clustering
4
Case Study

Ensemble Techniques

1
Boosting
2
Bagging
3
Random Forest
4
Case Study

Reinforcement Learning

1
Value based methods
2
Q-learning
3
Policy-based methods

Deep Learning

1
Neural Network Basics
2
Deep Neural Networks
3
TensorFlow using Neural Networks
4
Case Study

Natural Language Processing

1
Statistical NLP and text similarity
2
Text Summarization
3
Syntax and Parsing techniques
4
Semantics and Generation
5
Case Study

Computer Vision

1
Convolutional Neural Networks
2
Keras Library for Deep Learning in Python
3
Pre-processing Image Data
4
Object and face recognition using OpenCV
5
Case Study

intelligent Agents

1
Uniform and heuristic-based search techniques
2
Planning and constraint satisfaction techniques
3
Adversarial search and its uses
4
Case Study
No announcements at this moment.

Be the first to add a review.

Please, login to leave a review
This website uses cookies and asks your personal data to enhance your browsing experience.