Index
Prologue
Introduction
Module 1 - Classification
1. Definition and Classification of Artificial Intelligence
2. Machine Learning (ML)
3. Categories of algorithms in ML
4. Data
Module 2 - Methods
5. Big Data
6. Data Acquisition in 6 Steps
7. Natural Language Processing (NLP)
8. Internet of Things (IoT) (Internet of Things)
9. Methods of Artificial Intelligence
Module 3 - Diagrams in Machine Learning
10. Introduction to Visualization in Machine Learning
11. Scatter Plots
12. Histograms and Bar Charts
13. Box-Plots
14. Receiver Operating Characteristic (ROC)
15. Correlation Matrix and Heatmaps
16. Tree Diagrams
17. Dimensionality Reduction and Visualization
18. Flowcharts for Machine Learning Processes
19. Neural Network Architectures Diagrams
20. General Review
Module 4 - Software
21. Software
Module 5 - TinyML
22. What is TinyML?
23. Difference between traditional ML and TinyML
24. Platforms and Tools for TinyML
25. Optimization of Models for TinyML
26. Hardware Development for TinyML
27. Implementation of Models in Devices
28. Use Cases and Real Applications
29. Challenges and Limitations of TinyML
30. Future Trends and Advances in TinyML
31. Ethical and Privacy Aspects in TinyML
Module 6 - Use Cases
32. The Revolution of AI and ML in the Business World
33. Production Department
34. Research and Development Department (R&D)
35. Sales Department
36. Marketing Department
37. Human Resources Department (HR)
38. Finance Department
39. Logistics Department
40. Warehouse Department
41. Customer Service Department
42. Department of Information Technology (IT)
43. Purchasing Department
44. Quality Department
45. Legal Department
46. Documentation Department
47. Health and Safety Department
48. Maintenance Department
49. Administration Department
50. Department of Communication and Public Relations
51. Reception Department
52. Department of Management
Module 7 - Project Management
53. Introduction to Project Management in Artificial Intelligence Projects
54. Aspects to consider in an AI Project
55. Frameworks (Techniques for project management)
56. Resource Management
57. Risk Analysis
58. Management Control
59. Quality Management
60. Phases of a Project
61. Steps to Follow for the Successful Development of a Project.
62. Employee Acceptance of Artificial Intelligence
63. Roll-Out
Module 8 - Bias in Artificial Intelligence
64. Introduction to Bias
65. Bias and AI: a more detailed journey
Module 9 - Ethics and Law in the Field of Artificial Intelligence
66. Ethics and its Relationship with Artificial Intelligence
67. The Law and its Relationship with Artificial Intelligence
Acknowledgements
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