Course Description
The Rocheston Certified AI Engineer (RCAI) course from SecureNinja is a cutting-edge, hands-on training program designed to help participants build a strong foundation in artificial intelligence. This course covers essential AI concepts, including machine learning, deep learning, and natural language processing. Through practical exercises and real-world projects, participants will gain experience working with AI frameworks such as TensorFlow and PyTorch. The course also delves into data science, focusing on data manipulation, preprocessing, and model evaluation, equipping students with the tools to design and implement AI solutions in various industries.
Additionally, participants will explore AI’s role in industries like healthcare, finance, and cybersecurity, where they will learn how AI is transforming these sectors. Emphasis is also placed on the ethical implications of AI, covering important regulatory and compliance considerations to ensure responsible AI development.
Who Should Attend
This course is ideal for IT professionals, software developers, data scientists, AI engineers, and business leaders looking to integrate AI into their workflows. It is also beneficial for anyone aiming to improve their understanding of AI's impact on industries like healthcare, finance, cybersecurity, and beyond.
Prerequisites
Participants should have a basic understanding of Python programming, some exposure to mathematics (calculus and linear algebra), and probability. Familiarity with programming concepts and data science will be helpful but is not mandatory.
Duration
40 Hours
Course Outline
Module 1: Introduction to AI
- What is AI?
- History of AI
- AI applications
Module 2: Agents and Environments
- Intelligent Agents:
- Rational agents, PEAS, Single vs multiagents
- Learning agents, Reflex agents, Goal/Utility-based agents
- Intelligent Environments:
- Deterministic vs stochastic, Static vs dynamic environments
Module 3: Problem Solving Types
- Anatomy of a problem (Initial state, Actions, Goal test)
- Types of problems (Toy, Real-world)
Module 4: Problem Solving by Searching
- Uniformed vs informed searches
- Breadth-first, depth-first, iterative deepening
Module 5: Problem Solving Algorithms
- Local search, Hill-climbing, Genetic algorithm
Module 6: Gaming
- Game elements, decision-making, stochastic games
Module 7: Knowledge and Logic Agents
- Knowledge agents, Logic agents, The Wumpus world
Module 8: Propositional Logic
- Syntax/semantics, SAT problem solving, model checking
Module 9: First-Order Logic
- Syntax, semantics, knowledge engineering
Module 10: Scheduling & Planning
- Hierarchical task networks (HTN), Classical and multiagent planning
Module 11: Ontological Engineering
- Upper ontology, Categories, Events, and processes
Module 12: Decision Theory
- Uncertainty, Probability theory, Bayes’ rule
Module 13: Probability Theory
- Bayesian networks, Markov chain, Monte Carlo algorithms
Module 14: Utility Theory
- Multiattribute utility theory, Expert systems
Module 15: Game Theory
- Single-move, repeated games, Nash equilibrium
Module 16: Machine Learning
- Deep learning, Supervised/Unsupervised/Reinforced learning, Neural networks
Module 17: Natural Language Processing
- Information extraction, Deep semantic models, Vision-language intelligence
Module 18: Speech Recognition
- Acoustic modeling, Machine translation
Module 19: Image Processing
- Object recognition, 3D image reconstruction
Module 20: Robotics
- Robot hardware, software architectures
Module 21: IoT Integration
- Alexa, Google Home, Apple Homekit
Module 22: AI Toolkits
- Microsoft Cognitive Toolkit, PyTorch, TensorFlow
Module 23: Prime AI Applications
- Agriculture, Healthcare, Manufacturing, IT Service Management
Required Exams
Exam Number: RCAI-001
Number of Questions: 100 Multiple Choice
Exam Duration: 3 Hours
These training courses are only delivered as an onsite format for groups of 5 or more. Our world-class instructors will bring our on-demand turn-key solution directly to you. Contact us now for more details and pricing