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2 Days

(Online and onsite)

Price Upon Request
After completing this course, you will be able to:
- Understand the importance, principles, and fields of AI
- Implement basic Artificial Intelligence concepts with Python
- Apply regression and classification concepts to real-world problems
- Perform predictive analysis using decision trees and random forests
- Carry out clustering using the k-means and mean shift algorithms
- Understand the fundamentals of deep learning via practical examples
Lesson 1: Principles of Artificial Intelligence
- Fields and Applications of Artificial Intelligence
- AI Tools and Learning Models
- The Role of Python in Artificial Intelligence
- Python for Game AI
Lesson 2: AI with Search Techniques and Games
- Heuristics
- Pathfinding with the A* Algorithm
- Game AI with the Minmax Algorithm and Alpha-Beta Pruning
Lesson 3: Regression
- Linear Regression with One Variable
- Linear Regression with Multiple Variables
- Polynomial and Support Vector Regression
Lesson 4: Classification
- The Fundamentals of Classification
- Classification with Support Vector Machines
Lesson 5: Using Trees for Predictive Analysis
- Introduction to Decision Trees
- Random Forest Classifier
Lesson 6: Clustering
- Introduction to Clustering
- The k-means Algorithm
- Mean Shift Algorithm
Lesson 7: Deep Learning with Neural Networks
- TensorFlow for Python
- Introduction to Neural Networks
- Deep Learning
This course is for you if you Artificial Intelligence and Machine Learning Fundamentals is for software developers and data scientists who want to enrich their projects with machine learning. You do not need any prior experience in AI. However, it’s recommended that you have knowledge of high school-level mathematics and at least one programming language (preferably Python).
Hardware:
For the optimal student experience, we recommend the following hardware configuration:
- Processor: Intel Core i5 or equivalent
- Memory: 8 GB RAM
- Storage: 35 GB available space
- An internet connection
Software:
- OS: Windows 7 SP1 64-bit, Windows 8.1 64-bit or Windows 10 64-bit, Ubuntu
- Linux, or the latest version of macOS
- Browser: Google Chrome (latest version)
- Anaconda (latest version)
- IPython (latest version)
After completing this course, you will be able to:
- Understand the importance, principles, and fields of AI
- Implement basic Artificial Intelligence concepts with Python
- Apply regression and classification concepts to real-world problems
- Perform predictive analysis using decision trees and random forests
- Carry out clustering using the k-means and mean shift algorithms
- Understand the fundamentals of deep learning via practical examples
Lesson 1: Principles of Artificial Intelligence
- Fields and Applications of Artificial Intelligence
- AI Tools and Learning Models
- The Role of Python in Artificial Intelligence
- Python for Game AI
Lesson 2: AI with Search Techniques and Games
- Heuristics
- Pathfinding with the A* Algorithm
- Game AI with the Minmax Algorithm and Alpha-Beta Pruning
Lesson 3: Regression
- Linear Regression with One Variable
- Linear Regression with Multiple Variables
- Polynomial and Support Vector Regression
Lesson 4: Classification
- The Fundamentals of Classification
- Classification with Support Vector Machines
Lesson 5: Using Trees for Predictive Analysis
- Introduction to Decision Trees
- Random Forest Classifier
Lesson 6: Clustering
- Introduction to Clustering
- The k-means Algorithm
- Mean Shift Algorithm
Lesson 7: Deep Learning with Neural Networks
- TensorFlow for Python
- Introduction to Neural Networks
- Deep Learning
This course is for you if you Artificial Intelligence and Machine Learning Fundamentals is for software developers and data scientists who want to enrich their projects with machine learning. You do not need any prior experience in AI. However, it’s recommended that you have knowledge of high school-level mathematics and at least one programming language (preferably Python).
Hardware:
For the optimal student experience, we recommend the following hardware configuration:
- Processor: Intel Core i5 or equivalent
- Memory: 8 GB RAM
- Storage: 35 GB available space
- An internet connection
Software:
- OS: Windows 7 SP1 64-bit, Windows 8.1 64-bit or Windows 10 64-bit, Ubuntu
- Linux, or the latest version of macOS
- Browser: Google Chrome (latest version)
- Anaconda (latest version)
- IPython (latest version)