Artificial Intelligence
and Machine Learning
Fundamentals
Overview
Machine learning and neural networks are pillars on which you can build intelligent applications. Artificial Intelligence and Machine Learning Fundamentals begins by introducing you to Python and discussing AI search algorithms. You will cover in-depth mathematical topics, such as regression and classification, illustrated by Python examples.
As you make your way through the course, you will progress to advanced AI techniques and concepts, and work on real-life datasets to form decision trees and clusters. You will be introduced to neural networks, a powerful tool based on Moore’s law.
By the end of this course, you will be confident when it comes to building your own AI applications with your newly acquired skills!
Durasi Pelatihan: 3 Hari
• 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
This course takes a hands-on approach to implement different AI techniques and algorithms using Python. This course does not delve into the basics of Python. It is recommended to have knowledge of basic Python programming and high-school
mathematics.
Setelah mengikuti training ini, peserta akan bisa:
• Menerapkan konsep Cyber Security yang di dalamnya terdapat konsep Defense in-Depth untuk lebih menjaga keamanan organisasi secara lebih komprehensif.
• Menjelaskan porsi dan tanggung jawab masing-masing IT security profesional berdasarkan konsep Information Security dan Cyber Six, membedakan konsep bertahan (defense) dan menyerang (offense) di dalam konsep perang informasi (information warfare)
• Menjelaskan contoh dan penerapan bertahanan berlabis berdasarkan konsep Defense in-Depth sebagai bagian dari konsep Cyber Security
• Melakukan beberapa jenis dan metode serangan (Attacks) berdasarkan ancaman (Threats) dan juga Vulnerability di sisi target
• Menerapkan dan mengkonfigurasi Firewall, IDS, maupun Honeypots
• Melakukan vulnerability assessment, sebagai bagian dari proses risk management
• Melakukan Operating System Attacks, dengan menggunakan metode hacking tertentu untuk mempelajari taktik dan teknik yang dilakukan oleh Attacker
• Melakukan aktivitas hacking setelah mendapatkan informasi yang cukup tentang target dan melakukan hardening terhadap target
• Melakukan serangan terhadap web server dan web aplikasi termasuk bagaimana menghindari serangan dengan menerapkan keamanan di level web server maupun web aplikasi
• Membedakan konsep penetration testing dengan vulnerability assessment dan melakukan penetration testing terhadap web server dan web aplikasi dengan berbagai macam teknik
Lesson 1: Principles of Artificial Intelligence
• Fields and Applications of Artifcial Intelligence
• AI Tools and Learning Models
• The Role of Python in Artifcial Intelligence
• Python for Game AI
Lesson 2: AI with Search Techniques and Games
• Heuristics
• Pathfnding 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 Classifcation
• Classifcation with Support Vector Machines
Lesson 5: Using Trees for Predictive Analysis
• Introduction to Decision Trees
• Random Forest Classifer
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