Exploring Artificial Intelligence Training
Exploring Artificial Intelligence Training
Training Exploring Artificial Intelligence - Online E-Learning Course. Order and start immediately for the best price.
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Exploring Artificial Intelligence E-Learning
Order this amazing E-Learning Training Exploring Artificial Intelligence online course!
✔️ 1 year 24/7 access to rich interactive videos, voice, practice assignments, progress monitoring through reports and tests by topic to test your knowledge instantly.
✔️ After the course, you will receive a certificate of participation.
Why choose this course?
Artificial Intelligence (AI) has evolved in recent years from a theoretical field of research to a practical technology that affects almost all industries. With recent advances in computing power and algorithms, it is becoming increasingly accessible for developers and companies to build and apply AI solutions.
In this course, you will have the opportunity to learn the basics of AI and discover the techniques that make AI possible, from machine learning to expert systems. This learning path provides a clear introduction to AI problems and solutions, so you will develop the skills needed to get started with AI technologies.
What you will learn:
- Basics of Artificial Intelligence: Understand the fundamentals of AI and how it is used to solve complex problems.
- Machine Learning and Algorithms: Learn the core techniques behind machine learning, including supervised, unsupervised and reinforcement learning.
- Problem-solving approaches: Discover how AI techniques are used to tackle a variety of issues in different sectors.
- AI applications in business: Gain insight into how companies are applying AI for automation, data analysis and decision-making.
- Hands-on experience with AI techniques: Work with practical examples and exercises that apply theoretical knowledge in practice.
Who should participate?
This course is ideal for:
- Software developers who want to learn how to integrate AI technologies into their applications and systems.
- Data scientists who want to expand their knowledge with AI techniques and tools.
- AI enthusiasts who want to understand how artificial intelligence works and explore its applications in the real world.
- Business experts and managers who want to implement AI in their business strategies for a competitive advantage.
- IT professionals interested in building AI solutions for the future.
Course content
Introducing AI
Course: 31 Minutes
- Course Introduction
- What Is Artificial Intelligence?
- Fields and Applications
- AI Techniques
- Defining Agents
- Types of Agents
Environments
Course: 18 Minutes
- Describing Environments
- Environment's Observability
- Number of Agents in Environments
- Certainty in an Environment
- Environment's Behavior
Practice: Agents and Environments
Course: 3 Minutes
- Exercise: Describe an Agent and an Environment
Introducing Search Problems
Course: 15 Minutes
- Course Introduction
- Search Problems Defined
- Search Problem Examples
- Representing Search Problems for Search Algorithms
Brute Force Searching
Course: 9 Minutes
- Breadth-first Search
- Depth-first Search
- Iterative Deepening Search
Informed Searching
Course: 14 Minutes
- Greedy Best-first Search
- Heuristics
- Making Good Heuristics
- A* Search
Local Searching
Course: 5 Minutes
- Hill-climbing Search
- Simulated Annealing
Practice: Identifying Search Problems
Course: 2 Minutes
- Exercise: Describe Search Problems
Introducing CSPs
Course: 6 Minutes
- Course Introduction
- What Are Constraint Satisfaction Problems (CSPs)?
- Constraint Satisfaction Problem Examples
Solving CSPs
Course: 19 Minutes
- Backtracking Search
- Variable Ordering
- Arc Consistency
- Constraint Propagation
- Using Inference with Search
- Using a Local Search for CSPs
- Solving a Sudoku Puzzle
Practice: Constraint Satisfaction Problems
Course: 3 Minutes
- Exercise: Solve a Constraint Satisfaction Problem
- Course Introduction
- Adversarial Problems
- Adversarial Problem Representation
- Minimax Algorithm
- Alpha-beta Pruning
Imperfect Decisions
Course: 15 Minutes
- Evaluation Functions
- Cutoff Search
- Lookup Tables
- The Game of Chess
Stochastic Games
Course: 11 Minutes
- Expectiminimax Value
- Stochastic Evaluation Functions
- Monte Carlo Tree Search
Practice: Using the Minimax Algorithm
Course: 2 Minutes
- Exercise: Use Minimax and Pruning to Play a Game
Understanding Uncertainty
Course: 10 Minutes
- Course Introduction
- What Is Uncertainty?
- Uncertainty Representation
Understanding Utility Theory
Course: 13 Minutes
- Utility Theory
- Utility and Preferences
- Utility and Risks
- Value of Information
Examining the Markov Decision Process
Course: 21 Minutes
- Markov Chains
- Markov Decision Process
- MDP Value Iteration
- Partially Observable Markov Decision Process (POMDP)
- POMDP Value Iteration
- Applying POMDPs
Practice: Markov Decision Process
Course: 3 Minutes
- Exercise: Describe the Markov Decision Process
Learning for Computers
Course: 9 Minutes
- Course Introduction
- How Computers Can Learn
- Learning From Examples
Decision Trees
Course: 12 Minutes
- Using Decision Trees
- Decision Tree Learning: Information Gain
- Decision Tree Learning: Choosing Attributes
- Overfitting
Neural Networks
Course: 25 Minutes
- Artificial Neural Networks
- Neural Network Structure
- Types of Neural Networks
- Perceptron Learning
- Deep Neural Networks
- Convolutional Neural Networks
- Recurrent Neural Networks
Practice: Perceptron Training
Course: 2 Minutes
- Exercise: Make a Perceptron Learn From Examples
Introducing Reinforcement Learning
Course: 21 Minutes
- Course Introduction
- What Is Reinforcement Learning?
- Additive and Discounted Rewards
- Passive Learning
- Direct Utility Estimation
- Temporal Difference Learning
- Active Learning
- Exploration and Exploitation Policies
Q-learning Algorithm
Course: 12 Minutes
- Defining Q-learning
- Implementing Q-learning
- Off-policy and On-policy Learning
- Function Approximation
- Deep Q-learning
Practice: Q-learning
Course: 2 Minutes
- Exercise: Describe Q-learning
Defining NLP
Course: 17 Minutes
- Course Introduction
- Introducing Natural Language Processing (NLP)
- Base NLP Operations
- Porter Stemming Algorithm
- Named Entity Recognition
Basic Models
Course: 11 Minutes
- Building Natural Language Processing (NLP) Models
- Text Classification
- Naïve Bayes Classification
- Information Retrieval (IR)
Communication
Course: 14 Minutes
- Answering Questions
- Parsing
- Machine Translation
- Speech Recognition
Practice: NLP Operations
Course: 2 Minutes
- Exercise: Describe NLP Operations
Get started with Exploring Artificial Intelligence!
✔️ Learn at your own pace with rich interactive videos, speech and practice assignments.
✔️ Test your knowledge topic by topic with targeted tests and progress monitoring.
✔️ Get hands-on experience with AI solutions and discover how AI works in the real world.
✔️ Receive a certificate of participation upon successful completion of the course.
Order your course now and start your journey into the world of Artificial Intelligence!
| Language | English |
|---|---|
| Qualifications of the Instructor | Certified |
| Course Format and Length | Teaching videos with subtitles, interactive elements and assignments and tests |
| Lesson duration | 9 Hours |
| Progress monitoring | Yes |
| Access to Material | 365 days |
| Technical Requirements | Computer or mobile device, Stable internet connections Web browsersuch as Chrome, Firefox, Safari or Edge. |
| Support or Assistance | Helpdesk and online knowledge base 24/7 |
| Certification | Certificate of participation in PDF format |
| Price and costs | Course price at no extra cost |
| Cancellation policy and money-back guarantee | We assess this on a case-by-case basis |
| Award Winning E-learning | Yes |
| Tip! | Provide a quiet learning environment, time and motivation, audio equipment such as headphones or speakers for audio, account information such as login details to access the e-learning platform. |
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