Labs and Modules: What is Cybersecurity? ● Information Security Threats and Vulnerabilities ● Information Security Attacks ● Network Security Fundamentals ● Identification, Authentication, and Authorization ● Network Security Controls: Administrative Controls ● Network Security Controls: Physical Security ● Network Security Controls: Technical Controls ● Network Security Assessment Techniques and Tools ● Data Security ● Risk management ● Cyber Threat Project

Labs and Modules: Numeral Systems ● IP Addresses ● Network Services ● Shodan ● Google Dorks ● Hash and Encoding ● CMD Commands ● OSI Model ● Network Traffic ● (NetCraft) Project

Labs and Modules: Linux Commands ● Text Manipulation ● Searching ● Network Services ● Bash Scripts ● Files and Operations ● Scripting Project ● Tr

Labs and Modules: Advanced Manipulation ● Advanced Network Services ● Scanning ● Offline Brute-Force ● Advanced Admin Scripting ● Advanced Wireshark ● TCP/IP Model ● Online Attacks ● Trojans ● Firewalls ● (AnonyScan) Project ● Reading Network-Research Articles and Trend Analysis 

Labs and Modules: Information Gathering ● Host Discovery ● NMAP Ports Scanning  ● IDS ● Banner Grabbing ● Enumeration ● Exploitation ● Meterpreter ● Payloads ● Post Exploitation ● Social and Reverse Engineering ● WebApp Security ● (NetVul) Project (e.g., using NMAP, searchsploit, hydra, medusa, and others)

Labs and Modules: Understanding Data ● Regression ● Regularization ● Gradient Descent ● Feature Engineering ● Supervised Learning ● Boosting Models ● Classifier ● Clustering Algorithms ● Un/Semi-Supervised Learning ● Understanding Topics on Deep Learning and Reinforcement Learning

Primary Material: 

1. Stuart Russel, Peter Norvig. “Artificial Intelligence: A Modern Approach”, Fourth Edition, Global Edition.

2. Hands-On Machine Learning with Scikit-Learn, Keras, and TensorFlow, 2nd Edition

Supplementary:

3. Ian Goodfellow, Yoshua Bengio, Aaron Courville. "Deep Learning", MIT Press, 2016.