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Udemy - Ai Essentials For Business - OneDDL - 03-06-2025
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Free Download Udemy - Ai Essentials For Business
Published: 3/2025
MP4 | Video: h264, 1920x1080 | Audio: AAC, 44.1 KHz
Language: English | Size: 2.29 GB | Duration: 7h 46m
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!
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