What you'll learn

Become an AI and Machine Learning Engineer

Embark on an exciting journey into the realm of Artificial Intelligence (AI) and Machine Learning (ML) with our comprehensive course. Whether you're a beginner or an experienced professional, this course is designed to equip you with the knowledge and skills needed to thrive in the AI landscape.

What You'll Learn

Master ChatGPT from scratch, including over 1,000 prompts
Explore ChatGPT's new Plugins feature for enhanced functionality
Discover alternatives like Google Bard and Microsoft Bing Chat
Create stunning images using DALL-E and Midjourney
Utilize voice-based AI, avatars, music video AI, and more
Learn machine learning techniques using Microsoft Excel
Gain a comprehensive understanding of AI technology and its business applications
Understand AI ethics, risks, and challenges
Manage AI projects and teams effectively
Explore the future potential of AI and its impact on various industries

Course Overview

This course comprises 16 sections covering a wide range of AI and ML topics:

Introduction to the course and its objectives
Foundations of Artificial Intelligence
Exploration of ChatGPT
Understanding ChatGPT Plugins
Exploring alternatives to ChatGPT
Introduction to Excel and Machine Learning
Utilizing AI for image processing
Voice, avatars, and cloning applications
Exploring various AI applications
Using AI for business decisions
Ethical considerations in AI
AI applications in different industries
Machine Learning project lifecycle
Exploring the future of AI
Introduction to OpenAI API
Conclusion and additional AI topics

Course Requirements

No prior knowledge of AI or technical concepts is required, except for an optional section discussing OpenAI and APIs. The course is suitable for anyone interested in learning about AI and its applications.

How to Take the Course

The course offers three tracks - A for All, B for Basics, and C for ChatGPT. Choose the track that best suits your learning goals and preferences. Whether you want to delve deep into AI fundamentals or focus specifically on ChatGPT, we've got you covered.

Who Should Take This Course

This course is ideal for individuals looking to enhance their understanding of AI and ML, whether for career advancement or personal enrichment. Whether you're a business professional, developer, or student, this course will empower you to harness the power of AI to drive innovation and success.

Don't miss this opportunity to become an AI and Machine Learning Engineer. Enroll now and embark on an exciting journey into the future of technology!

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Course Content

1WELCO~1

1.1 Book Called The Complete Artificial Intelligence Book

1.2 Index of AI Topics

1. [AB] Introduction to AI (What, Why and How of Section 2)

2_ABC_~1

3. [AB] A.I. vs Machine Learning vs. Deep Learning

4. [AB] Exercise on Machine Learning & Netflix

4.5 Web Traffic Anomalies

5_A_SU~1

6. [A] Exercise on Machine Learning Clustering

6.2 Mall_Customers

7. [AB] Computer Vision (Using Tesla as an Example)

8. [AB] Exercise on Computer Vision

9. [A] Natural Language Processing (NLP) and NLP Applications

10_AB_~1

11. [A] AutoML and Transfer Learning

12_AB_~1

13. [AB] Challenges and Limitations of AI

14. [AB] Job Positions in the Data World

1. [ABC] Introduction to ChatGPT (What, Why and How of Section 3)

2. [ABC] Introduction to Prompt Engineering (Basic and Advanced Prompts)

3. [ABC] ChatGPT User Interface and Account Setup

4. [ABC] Important ProblemsIssues with Using ChatGPT

5. [ABC] Your First Prompt Exercise - Directional Prompting

6. [ABC] Role Playing

7. [ABC] Few-Shot Prompting

8. [ABC] Putting It All Together & Ask Me If Needed Technique

9. [ABC] Now You Try! (Exercise)

9.1 Exercise Instructions

10. [ABC] Exercise Solution

11. [AC] Chain of Thought Prompting

12. [AC] In Style of Prompting

13. [AC] Structuring Your Data & Using Tables

14. [ABC] Text Summarization

15. [AC] Text Classification

16. [AC] Coding Generation

17. [AC] ChatGPT Hacking

18. [AC] Additional ChatGPT Tips

19. [AC] Large Language Models [Optional Lecture]

20. [AC] How Computers Understand Text [Optional Lecture]

21. [AC] What Happens When ChatGPT Receives a Prompt [Optional Lecture]

1. [AC] Introduction to ChatGPT Plugins (What, Why and How of Section 4)

2. [AC] What are ChatGPT Plugins and How to Get Them

3. [AC] Browsing with ChatGPT

4. [AC] Wolfram Plugin for ChatGPT

5. [AC] Exercise on Wolfram Plugin for ChatGPT

6. [AC] edX Plugin for ChatGPT

7. [AC] Exercise on edX Plugin

8. [AC] KAYAK Plugin for ChatGPT

9. [AC] Exercise on KAYAK Plugin

10. [AC] Zillow Plugin for ChatGPT

11. [AC] Exercise on Zillow Plugin

12. [AC] Podcast Search Plugin for ChatGPT

1. [AC] Introduction to ChatGPT Alternatives (What, Why and How of Section 5)

2. [AC] Bard by Google

2.1 Google's Bard Link

3. [AC] Exercise on Using Bard

3.1 Google's Bard Link

4. [AC] Bing Chat by Microsoft

4.1 Bing Chat (Edge Browser Download) Link

5. S5L5 [AC] Exercise on Using Bing Chat

5.1 Bing Chat (Edge Browser Download) Link

1. [AB] Intro to Using Excel and Machine Learning (What, Why and How of Section 6)

2. [AB] Basic Linear Regression Analysis in Excel

2.1 Rain_Data

3. [AB] Exercise on Basic Regression Analysis in Excel

3.1 Nesting_Doll_Data

4. [AB] Answer to Exercise on Basic Regression Analysis in Excel

5. [A] Advanced Regression Analysis in Excel Part 1

5.1 Rain_Data

6. [A] Advanced Regression Analysis in Excel Part 2

7. [A] Advanced Regression Analysis in Excel Part 3

8. [A] Exercise on Advanced Regression Analysis in Excel

8.1 Nesting_Doll_Data

9. [A] Answer to Exercise on Advanced Regression Analysis in Excel

10. [A] Multiple Regression Analysis in Excel Part 1

10.1 Rain_Multiple_Regression_Data

11. [A] Multiple Regression Analysis in Excel Part 2

12. [A] Exercise on Multiple Regression Analysis in Excel

12.1 Multiple_Regression_Nesting_Doll_Data

13. [A] Answer to Exercise on Multiple Regression Analysis in Excel

14. [A] Fixing Problems with Data

1. [AB] Intro to Images & AI (What, Why and How of Section 7)

2. [AB] Midjourney Account Setup

3. [AB] Midjourney Interface Walkthrough and How to Use it

4. [AB] Midjourney Good Prompting Practices

5. [AB] Midjourney Image Prompting

6. [AB] Exercise on Midjourney Image Prompting

7. [AB] Answer to Exercise on Midjourney Image Prompting

8. [A] Midjourney Image Blending

9. [A] Midjourney Image Captioning (Meaning Description Feature)

10. [A] Midjourney Advanced Settings

11. [A] Midjourney Negative Prompting

12. [A] Midjourney Other Commands Aspect Ratios & More)

13. [A] Advanced Exercise on Midjourney

14. [A] Answer to Advanced Exercise on Midjourney

15. [AB] DALL-E 2 Account Setup and Interface Walkthrough

16. [AB] DALL-E 2 Prompt Designs

17. [AB] Exercise on DALL-E 2

18. [AB] Answer to Exercise on DALL-E 2

19. [A] DALL-E 2 Editing Images & Outpainting

20. [A] DALL-E 2 Image Inpainting

21. [A] Advanced Exercise on DALL-E 2

22. [A] Answer to Advanced Exercise on DALL-E 2

1. [AB] Intro to Voice, Avatars & Cloning (What, Why and How of Section 8)

2. [AB] UsingMaking AI Avatars with D-ID

3. [AB] Exercise on D-ID

4. [AB] Resemble AI

5. [AB] Exercise on Resemble AI

6. [AB] ElevenLabs

7. [AB] Exercise on ElevenLabs

1_A_IN~1

2. [A] Ralph AI

3. [A] Exercise on Ralph AI

4. [A] Answer to Exercise on Ralph AI

5. [A] Making Music Videos with AI

6. [A] Exercise on Making Music Videos with AI

7. [A] Chatbase (How to Add Chatbase GPT to Your Website)

8. [A] Exercise on Chatbase

9. [A] Auto GPT

10. [A] Exercise on Auto GPT

11. [A] Character AI

1. [AB] Intro to Using AI for Business Decisions (What, Why and How of Section 10)

2. [AB] The Role of AI in Business Strategy

3. [AB] Aligning AI Initiatives with Business Objectives

4. [AB] Identifying AI Opportunities

5. [AB] Setting AI KPIs

6. [AB] Building a Data-Driven OrganizationCulture

7. [AB] Selecting the Right AI Solutions and Vendors

8. [AB] Overcoming Challenges in AI Implementation

9. [AB] AI Ethics, Governance, and Compliance

10. [AB] Data Drift

11. [AB] Risks and Cost of Having AI in Production

12. [AB] Monitoring and Evaluating AI Performance

1. [AB] Intro to Additional Risks & Ethics with AI

2. [AB] Bias

3. [AB] Explainability and Interpretability

4. [AB] Data Privacy and Security in AI

1. [AB] AI in Insurance

2. [AB] AI in Finance and Banking

3. [AB] AI in Retail

4. [AB] AI in Marketing

5. [AB] AI in Supply Chain

1. [A] Intro to Machine Learning Project Lifecycle

2. [A] General Overview

3. [A] Data Collection

4. [A] Model Training

5. [A] Model Evaluation

6. [A] Model Deployment

7. [A] Model Monitoring

1. [AB] Overview of 13 Emerging AI Technologies

2. [AB] Preparing for the Future of AI

3. [AB] Where We See AI Being UsedDeployed and How

1. [A] Intro to OpenAI API

2. [A] What is an API & the Pricing Model

3. [A] Using API from Python and Sending the First Request

4. [A] Making our Toy ChatGPT (Customer Support Chatbot)

5. [A] Talking about Embeddings and Fine Tuning

1. [AB] Conclusion and Additional AI Topics

Course Comments

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Enrolled2
Lectures145
LanguageEnglish
Duration4 - 8 months
CertificateYes
Pass Percentage70 %

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