Ai Essentials For Business

Drive AI Innovation to 10x Your Business!

What you'll learn

Understand AI Fundamentals – Grasp the core concepts, types, and evolution of AI, including machine learning and deep learning.

Identify AI Business Opportunities – Recognize how AI can drive innovation and efficiency across various business functions.

Explore AI Applications – Analyze industry-specific use cases in marketing, sales, operations, finance, HR, customer service, and more.

Develop an AI Strategy – Create a structured approach to adopting AI solutions, selecting the right technologies, and aligning AI with business goals.

Implement AI Ethically and Effectively – Understand ethical considerations, legal compliance, and data privacy to ensure responsible AI deployment.

Navigate AI Tools and Technologies – Explore AI platforms, no-code solutions, and data analytics tools tailored for business professionals.

Prepare for the Future of AI – Stay ahead of emerging AI trends and foster an AI-ready culture within the organization.

Requirements

No requirements - only an interest in AI & Business

Description

AI Essentials for Business is a self-paced online course designed to help business professionals understand and apply artificial intelligence (AI) in practical, real-world scenarios. Whether you're a business leader, manager, entrepreneur, or professional looking to stay ahead in the rapidly evolving digital landscape, this course provides a strong foundation in AI and its business applications.We break down complex AI concepts into clear, easy-to-understand lessons, covering essential topics such as machine learning, deep learning, and data-driven decision-making. You'll explore how AI is transforming key industries like marketing, finance, operations, human resources, and customer service, gaining insights into how businesses are using AI to improve efficiency, automate processes, and enhance customer experiences.Beyond understanding AI, this course also provides a strategic roadmap for successfully integrating AI into business operations. You’ll learn how to identify AI opportunities, assess business processes for AI adoption, select the right tools, and implement AI solutions effectively. Ethical considerations, legal compliance, and data privacy are also covered to ensure responsible AI use.With interactive modules, case studies, expert insights, and hands-on exercises, you’ll develop the confidence to leverage AI for smarter decision-making and long-term business growth. By the end of the course, you’ll have the knowledge and skills to create an AI strategy, drive innovation, and make AI a valuable asset in your organization. Whether you're new to AI or looking to deepen your understanding, this course will equip you with the tools to stay competitive in an AI-driven world.

Overview

Section 1: Introduction

Lecture 1 1.1.1 What is AI?

Lecture 2 1.1.2 The Historical Evolution of AI

Lecture 3 1.1.3 Two types of AI

Lecture 4 1.1.4 Types of AI - A General Overview

Lecture 5 1.1.5 Types of AI - Machine Learning (ML)

Lecture 6 1.1.6 Types of AI - Deep Learning

Lecture 7 1.1.7 Types of AI - Natural Language Processing (NLP)

Lecture 8 1.1.8 AI as a Driver of Digital Business Transformation

Lecture 9 1.1.9 AI as a Competitive Edge

Lecture 10 1.1.10 Assessing AI Business Opportunities - the IBM Framework

Section 2: Fundamentals of Machine Learning

Lecture 11 2.1 Machine Learning Basics and AI Use Cases

Lecture 12 2.2 Key Concepts in Machine Learning (ML)

Lecture 13 2.3 Supervised Learning

Lecture 14 2.4 Unsupervised Learning

Lecture 15 2.5 Reinforcement Learning

Lecture 16 2.6 How Machines Learn from Data

Lecture 17 2.7 Common Machine Learning (ML) Algorithms - Supervised Learning

Lecture 18 2.8 Common Machine Learning (ML) Algorithms - Unsupervised Learning

Lecture 19 2.9 Common Machine Learning (ML) Algorithms - Reinforcement Learning

Lecture 20 2.10 AI Model Training, Validation and Evaluation

Lecture 21 2.11 Practical Example - Building an AI Customer Churn Prediction Model (Roadmap

Section 3: Deep Learning

Lecture 22 3.1 Deep Learning Essentials - I

Lecture 23 3.2 Deep Learning Essentials - II

Lecture 24 3.3 Neural Networks and their Business Applications

Lecture 25 3.4 Challenges in Implementing Neural Networks

Lecture 26 3.5 Data Quality, Quantity and Pre-processing

Lecture 27 3.6 Data Management - Best Practices

Section 4: AI Business Applications

Lecture 28 4.1 AI Applications - Marketing and Sales

Lecture 29 4.2 AI Applications - Business Operations and Supply Chain Management

Lecture 30 4.3 AI Applications - Human Resources

Lecture 31 4.4 AI Applications - Finance and Risk Management

Lecture 32 4.5 Identifying AI Business Opportunities

Lecture 33 4.6 Implementing AI in Business - Goals and KPIs

Lecture 34 4.7 Developing an AI Roadmap

Lecture 35 4.8 Developing an AI Roadmap - Resource Allocation

Lecture 36 4.9 Exercise - Developing an AI Strategy

Lecture 37 4.10 Example - Developing an AI Strategy (I)

Lecture 38 4.11 Example - Developing an AI Strategy (II)

Lecture 39 4.12 Example - Developing an AI Strategy (III)

Lecture 40 4.13 Example - Developing an AI Strategy (IV)

Lecture 41 4.14 Example - Developing an AI Strategy (Key Take-aways)

Lecture 42 4.15 Selecting AI Technologies

Lecture 43 4.16 In-house Development vs Outsourcing

Lecture 44 4.17 Hybrid Approach to AI Development

Lecture 45 4.18 Deciding whether to develop in-house or outsource

Lecture 46 4.19 Example - Deciding how to develop AI

Section 5: Ethical and Legal Aspects of AI

Lecture 47 5.1 Ethical Practices in AI - Bias

Lecture 48 5.2 Ethical Practices in AI - Transparency and Explainability

Lecture 49 5.3.1 Data Privacy and Security - The GDPR

Lecture 50 5.3.2 Data Privacy and Security - The CCPA

Lecture 51 5.3.3 Data Privacy and Security - Security Considerations

Lecture 52 5.4 Societal Considerations of AI

Lecture 53 5.5 Impact of AI (Example)

Lecture 54 5.6 Corporate Social Responsibility (CSR) and AI

Lecture 55 5.7. 1 Developing an AI Ethics Policy

Lecture 56 5.7.2 Exercise - Developing an AI Ethics Policy

Lecture 57 5.7.3 Exercise - Developing an AI Ethics Policy - Example

Everyone interested in AI and its business applications!