Artificial intelligence (AI) has been one of the core research techniques in computer science since the beginning of the field, and in recent years an emergence in research and computational power has made AI development more accessible for developers.
In this certification course, you will learn the foundation of Artificial Intelligence (AI) and the techniques used to make AI solve problems.
You will receive online access to e-learning (videos), hard copy material is not applicable to this course.
Why should one take Artificial Intelligence Certification?
This Course is intended for web developers, programmers and graduates wanting to excel in their chosen areas. It is also well suited for those who are already working and would like to take certification for further career progression.
Earning Vskills Artificial Intelligence Certification can help candidate differentiate in today's competitive job market, broaden their employment opportunities by displaying their advanced skills, and result in higher earning potential.
Who will benefit from taking Artificial Intelligence Certification?
Job seekers looking to find employment in IT or software development departments of various companies, students who want to learn Artificial Intelligence.
Companies that hire Vskills Certified Artificial Intelligence Professionals
Artificial Intelligence professionals are in great demand. It is the most popular core research techniques in computer science. Companies like Accenture, KPMG, Amazon, IBM, Ericsson and Wipro etc specializing in Data Science are constantly looking for certified professionals in Artificial Intelligence.
Artificial Intelligence Table of Contents
Artificial Intelligence Sample Questions
Artificial Intelligence Interview Questions
Apply for Artificial Intelligence Professional Certification
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TABLE OF CONTENT
INTRODUCTION TO ARTIFICIAL INTELLIGENCE AND JAVA
- The Course Overview
- Understanding AI Problems Related to Supervised/Unsupervised Learning
- Difference between Classification and Regression
- Installing JDK and JRE
- Setting Up of Netbeans IDE
- Import Java Libraries and Export Code Projects as JAR Files
- Introduction to Search
- Implementation of Dijkstra’s Search
- Understand the Notion of Heuristics
- Brief Introduction of A* Algorithm
- Implementation of A* Algorithm
AI GAMES AND RULE BASED SYSTEM
- Introduction of Min-Max Algorithm
- Implementation of Min-Max Algorithm Using an Example
- Installing Prolog
- Introduction of Rule-Based Systems with Prolog
- Setting Up the Prolog with Java
- Executing Prolog Queries Using Java
INTERFACING WITH WEKA
- Brief Introduction to Weka
- Installing and Interfacing with Weka
- Reading and Writing Datasets
- Converting Datasets
- Filtering Attributes
- Discretizing Attributes
- Attribute Selection
- Developing a Classifier
- Model Evaluation
- Making Predictions
- Saving/Loading Models
SEMI-SUPERVISED AND UNSUPERVISED LEARNING
- Working with K-means Clustering
- Evaluating a Clustering Model
- Introduction to Semi-Supervised Learning
- Difference Between Unsupervised and Semi-Supervised Learning
- Self-training/Co-training Machine Learning Models
- Making Predictions with Semi-Supervised Machine Learning Models