BCS Essentials Certificate in Artificial Intelligence Preparation

• No prerequisites required

Audience

• IT professionals
• Business analysts
• Project managers

The BCS Essentials Certificate in Artificial Intelligence is an entry-level certification course that provides foundational knowledge of AI concepts, including basic terminology, the process of machine learning, and the ethical considerations surrounding AI projects.

This instructor-led, live training (online or onsite) is aimed at beginner-level IT professionals who wish to learn about the potential benefits, risks, and challenges of implementing AI projects.

By the end of this training, participants will be able to:

• Understand the fundamental concepts, techniques, and ethical considerations of AI.
• Be familiar with real-world applications and challenges in AI.
• Gain confidence to take the BCS Essentials Certificate in Artificial Intelligence exam.
• Develop a practical approach to AI implementation in their professional environments.

NobleProg is a BCS Accredited Training Provider.
This course will be delivered by an expert NobleProg trainer approved by BCS.

Format of the Course

• Interactive lecture and discussion.
• Lots of exercises and practice.
• Hands-on implementation in a live-lab environment.

Course Customization Options

• To request a customized training for this course, please contact us to arrange.

Introduction to AI

• What is Artificial Intelligence?
• Key milestones in AI development
• AI vs. Machine Learning vs. Deep Learning
• Types of AI: Narrow AI, General AI, and Superintelligent AI

Fundamental AI Concepts

• Data, Algorithms, and Models
• Machine Learning fundamentals: Supervised, Unsupervised, and Reinforcement Learning
• Neural networks and Deep Learning basics
• Natural Language Processing (NLP) overview

AI Applications in Real World

• AI in healthcare, finance, retail, and transportation
• Intelligent virtual assistants and chatbots
• AI in business analytics and decision-making

Preparing Data for AI

• Data quality and preprocessing
• Structured vs. unstructured data
• Data ethics and biases
• Data collection and labeling methods

AI Ethics and Governance

• Ethical concerns in AI development
• Bias in AI models and algorithms
• Regulatory frameworks and governance in AI
• AI accountability and transparency

AI Tools and Technologies

• Overview of popular AI frameworks
• Introduction to AI platforms (Google AI, Microsoft Azure, IBM Watson)
• Basics of automation and RPA (Robotic Process Automation)

AI Risks, Security, and Challenges

• Security challenges in AI systems
• Risks of over-reliance on AI
• Socioeconomic impact of AI adoption
• AI model performance issues and monitoring

BCS Exam Preparation and Practice

• BCS exam format and structure
• Sample questions and practice quizzes
• Key areas to focus on for the exam
• Final preparation tips and strategies

Summary and Next Steps