Best Ethical AI Courses to Learn in February 2025
Looking to enhance your skills? We’ve curated a list of the top-rated ethical AI courses available this month. These courses are highly rated by students and offer comprehensive learning experiences.
10. AI Video School Complete Beginner to Pro, Sora Runway & more
Instructor: Dan Britain
Master AI videos creation with step-by-step expert guidance, mastering 30+ top AI tools—and the list keeps growing!
Course Highlights:
- Rating: 4.79 ⭐ (141 reviews)
- Students Enrolled: 1320
- Course Length: 67602 hours
- Number of Lectures: 132
- Number of Quizzes: 0
AI Video School Complete Beginner to Pro, Sora Runway & more, has an average rating of 4.79, with 132 lectures, based on 141 reviews, and has 1320 subscribers.
You will learn about Understand AI Video Basics: Grasp fundamental concepts of AI video creation and its growing importance in content production. Master AI Workflows: Learn structured workflows tailored to various project needs like social media, ads, and storytelling. Generate Creative Video Ideas: Use tools like ChatGPT, Claude, and Gemini to brainstorm unique and engaging video concepts. Write AI-Enhanced Scripts: Develop compelling scripts with AI tools like ChatGPT, Scribbler, and ChatSonic. Create Consistent Mood Boards: Design mood boards for visual planning using tools like MidJourney and Photoshop. Produce Realistic AI Images: Master image generation as a foundation for AI videos with tools like DALL·E and Stable Diffusion. Generate Professional AI Videos: Use Runway ML, Sora, and other tools to create polished videos from your ideas. Enhance Videos with AI Audio: Generate music, sound effects, and voiceovers to elevate the quality of your projects. Upscale Videos: Refine your AI videos with editing and upscaling techniques for professional results. Create a Complete AI Project: Follow along to produce your own video, learning step-by-step from idea to final output. This course is ideal for individuals who are Complete Beginners: Anyone curious about AI video creation with no prior experience—start from scratch and master the basics. or Content Creators: YouTubers, TikTokers, or social media influencers looking to elevate their videos with cutting-edge AI tools. or Aspiring Filmmakers: Individuals interested in storytelling or creating short films with AI as a powerful creative assistant. or Marketing Professionals: Those seeking to produce engaging, high-quality ads or brand content quickly and efficiently. or Freelancers: Independent professionals aiming to add AI video production to their service offerings and attract more clients. or Career Changers: Those looking to break into a growing and innovative field with high-demand skills. or Video Editors: Professionals who want to integrate AI tools into their editing workflows to save time and expand creative possibilities. or AI Enthusiasts: Individuals eager to explore practical applications of AI in a fast-evolving field. or Students: Learners aiming to build future-ready skills in AI video production for career or personal projects. It is particularly useful for Complete Beginners: Anyone curious about AI video creation with no prior experience—start from scratch and master the basics. or Content Creators: YouTubers, TikTokers, or social media influencers looking to elevate their videos with cutting-edge AI tools. or Aspiring Filmmakers: Individuals interested in storytelling or creating short films with AI as a powerful creative assistant. or Marketing Professionals: Those seeking to produce engaging, high-quality ads or brand content quickly and efficiently. or Freelancers: Independent professionals aiming to add AI video production to their service offerings and attract more clients. or Career Changers: Those looking to break into a growing and innovative field with high-demand skills. or Video Editors: Professionals who want to integrate AI tools into their editing workflows to save time and expand creative possibilities. or AI Enthusiasts: Individuals eager to explore practical applications of AI in a fast-evolving field. or Students: Learners aiming to build future-ready skills in AI video production for career or personal projects.
Learn More About AI Video School Complete Beginner to Pro, Sora Runway & more
What You Will Learn
- Understand AI Video Basics: Grasp fundamental concepts of AI video creation and its growing importance in content production.
- Master AI Workflows: Learn structured workflows tailored to various project needs like social media, ads, and storytelling.
- Generate Creative Video Ideas: Use tools like ChatGPT, Claude, and Gemini to brainstorm unique and engaging video concepts.
- Write AI-Enhanced Scripts: Develop compelling scripts with AI tools like ChatGPT, Scribbler, and ChatSonic.
- Create Consistent Mood Boards: Design mood boards for visual planning using tools like MidJourney and Photoshop.
- Produce Realistic AI Images: Master image generation as a foundation for AI videos with tools like DALL·E and Stable Diffusion.
- Generate Professional AI Videos: Use Runway ML, Sora, and other tools to create polished videos from your ideas.
- Enhance Videos with AI Audio: Generate music, sound effects, and voiceovers to elevate the quality of your projects.
- Upscale Videos: Refine your AI videos with editing and upscaling techniques for professional results.
- Create a Complete AI Project: Follow along to produce your own video, learning step-by-step from idea to final output.
9. Complete Generative AI Course With Langchain and Huggingface
Instructor: Krish Naik
Complete Guide to Building, Deploying, and Optimizing Generative AI with Langchain and Huggingface
Course Highlights:
- Rating: 4.61 ⭐ (6171 reviews)
- Students Enrolled: 49007
- Course Length: 194803 hours
- Number of Lectures: 207
- Number of Quizzes: 0
Complete Generative AI Course With Langchain and Huggingface, has an average rating of 4.61, with 207 lectures, based on 6171 reviews, and has 49007 subscribers.
You will learn about Learn to create advanced generative AI applications leveraging the Langchain framework and Huggingface's state-of-the-art models. Understand the architecture and design patterns for building robust generative AI systems. Gain hands-on experience in deploying generative AI models to various environments, including cloud platforms and on-premise servers. Explore different deployment strategies, ensuring scalability and reliability of AI applications. Develop Retrieval-Augmented Generation (RAG) pipelines to enhance the performance and accuracy of generative models by integrating retrieval mechanisms. Learn to seamlessly incorporate Huggingface's pre-trained models into Langchain applications, leveraging their powerful NLP capabilities. Customize and fine-tune Huggingface models to fit specific application requirements and use cases. Work on real-world projects that illustrate the application of generative AI in various domains, such as chatbots, content generation, and data augmentation. This course is ideal for individuals who are Individuals passionate about AI and ML who want to expand their knowledge and skills in generative AI applications. or Professionals looking to enhance their expertise in building and deploying generative AI models, particularly using Langchain and Huggingface. or Developers interested in integrating advanced AI capabilities into their applications and learning about the deployment and optimization of AI models. It is particularly useful for Individuals passionate about AI and ML who want to expand their knowledge and skills in generative AI applications. or Professionals looking to enhance their expertise in building and deploying generative AI models, particularly using Langchain and Huggingface. or Developers interested in integrating advanced AI capabilities into their applications and learning about the deployment and optimization of AI models.
Learn More About Complete Generative AI Course With Langchain and Huggingface
What You Will Learn
- Learn to create advanced generative AI applications leveraging the Langchain framework and Huggingface's state-of-the-art models.
- Understand the architecture and design patterns for building robust generative AI systems.
- Gain hands-on experience in deploying generative AI models to various environments, including cloud platforms and on-premise servers.
- Explore different deployment strategies, ensuring scalability and reliability of AI applications.
- Develop Retrieval-Augmented Generation (RAG) pipelines to enhance the performance and accuracy of generative models by integrating retrieval mechanisms.
- Learn to seamlessly incorporate Huggingface's pre-trained models into Langchain applications, leveraging their powerful NLP capabilities.
- Customize and fine-tune Huggingface models to fit specific application requirements and use cases.
- Work on real-world projects that illustrate the application of generative AI in various domains, such as chatbots, content generation, and data augmentation.
8. Artificial Intelligence & ChatGPT for Cyber Security 2025
Instructor: Luka Anicin
Master Cyber Security/Ethical Hacking With Artificial Intelligence – Implement, Uncover Risks and Navigate The AI Era
Course Highlights:
- Rating: 4.57 ⭐ (2527 reviews)
- Students Enrolled: 9435
- Course Length: 25061 hours
- Number of Lectures: 81
- Number of Quizzes: 7
Artificial Intelligence & ChatGPT for Cyber Security 2025, has an average rating of 4.57, with 81 lectures, 7 quizzes, based on 2527 reviews, and has 9435 subscribers.
You will learn about Learn ChatGPT for Cyber Security Learn Prompt Engineering Use Advanced ChatGPT functionality Implement Bypassing ChatGPT filters Learn Social Engineering with Artificial Intelligence Create a Voice Clone with AI Create Deepfake Videos For Social Engineering with AI Learn AI Based SIEM Learn AI Based Firewalls Learn Email Filtering with AI Learn AI In Identity and Access Management Build an Email Filtering System with AI and Python Build a Phishing detection system with AI and Python Implement Artificial Intelligence in Network Security Using Logistic Regression Algorithm for Network Monitoring Create Malware Detection system with AI and Python Learn Decision Trees Algorithm Learn K-Nearest Neighbors Algorithm KNN Learn Data Poisoning Attack Cover Data Bias Vulnerability Learn Model Vulnerabilities Cover Ethical Concerns of Artificial Intelligence and ChatGPT Learn Basics of Cyber Security Learn Basics of Artificial Intelligence Learn Basics of Python Programming This course is ideal for individuals who are Anyone Interested In Cyber Security or Anyone Interested In Artificial Intelligence or Anyone Interested In Applying AI In Cyber Security or Anyone Who Wants To Learn About Threats and Vulnerabilities In Artificial Intelligence or Anyone Who Wants To Learn How To Combine Python With AI To Develop Cyber Security Tools Like: Network Monitoring System, Phishing Detection System, Malware Detection System, Email Filtering System It is particularly useful for Anyone Interested In Cyber Security or Anyone Interested In Artificial Intelligence or Anyone Interested In Applying AI In Cyber Security or Anyone Who Wants To Learn About Threats and Vulnerabilities In Artificial Intelligence or Anyone Who Wants To Learn How To Combine Python With AI To Develop Cyber Security Tools Like: Network Monitoring System, Phishing Detection System, Malware Detection System, Email Filtering System.
Learn More About Artificial Intelligence & ChatGPT for Cyber Security 2025
What You Will Learn
- Learn ChatGPT for Cyber Security
- Learn Prompt Engineering
- Use Advanced ChatGPT functionality
- Implement Bypassing ChatGPT filters
- Learn Social Engineering with Artificial Intelligence
- Create a Voice Clone with AI
- Create Deepfake Videos For Social Engineering with AI
- Learn AI Based SIEM
- Learn AI Based Firewalls
- Learn Email Filtering with AI
- Learn AI In Identity and Access Management
- Build an Email Filtering System with AI and Python
- Build a Phishing detection system with AI and Python
- Implement Artificial Intelligence in Network Security
- Using Logistic Regression Algorithm for Network Monitoring
- Create Malware Detection system with AI and Python
- Learn Decision Trees Algorithm
- Learn K-Nearest Neighbors Algorithm KNN
- Learn Data Poisoning Attack
- Cover Data Bias Vulnerability
- Learn Model Vulnerabilities
- Cover Ethical Concerns of Artificial Intelligence and ChatGPT
- Learn Basics of Cyber Security
- Learn Basics of Artificial Intelligence
- Learn Basics of Python Programming
7. Diffusion Mastery: Flux, Stable Diffusion, Midjourney & more
Instructor: Arnold Oberleiter
AI Art and Videos: Stable Diffusion, Runway, Flux, ComfyUI, Forge WebUI, MidJourney, DALL-E, Adobe Firefly a. LeonardoAI
Course Highlights:
- Rating: 4.81 ⭐ (265 reviews)
- Students Enrolled: 2159
- Course Length: 78900 hours
- Number of Lectures: 181
- Number of Quizzes: 0
Diffusion Mastery: Flux, Stable Diffusion, Midjourney & more, has an average rating of 4.81, with 181 lectures, based on 265 reviews, and has 2159 subscribers.
You will learn about Introduction to Diffusion Models: Basics and first steps with diffusion models Prompt Engineering: Optimizing prompts for various platforms like DALL-E, MidJourney, Flux, and Stable Diffusion Stable Diffusion & Flux: Using open-source models, negative prompts, LoRAs for SDXL or Flux Guides for installing and using tools like Fooocus, ComfyUI, Forge, locally or in the cloud Flux: Usage for inpainting, IP Adapter, ControlNets, custom LoRAs, and more Training custom models & LoRAs, checkpoints, encoders, inpainting and upscaling, multiline prompts for creative image generation Creative Applications: Creating consistent characters, AI influencers, product placements, changing clothes and styles (e.g., anime) Specialized workflows and tools: Using tools like ComfyUI, Forge, Fooocus, integrating ControlNets, advanced prompting, and logo design Platforms: Utilizing Leonardo AI, MidJourney, Ideogram, Adobe Firefly, Google Colab, SeaArt, Replicate, and more Deepfakes: Faceswapping in photos and videos, installing programs for live deepfakes in Python, voice cloning, and legal concerns AI voices and music: Creating audiobooks, sound effects, and music with tools like Elevenlabs, Suno, Udio, and OpenAI API AI videos: Producing AI films with Hotshot, Kling AI, Runway, Pika, Dreammachine, Deforum, WrapFusion, Heygen, and more Upscaling and sound enhancement: Improving image, video, and sound quality, higher resolution, or converting to vector formats Ethics and security: Legal frameworks and data protection in the use of diffusion models This course is ideal for individuals who are Anyone who wants to learn about AI or Technology enthusiasts who want to stay at the forefront of the latest AI developments or Artists and creatives looking to explore new dimensions of art with AI or Developers and designers who want to expand the possibilities of diffusion models It is particularly useful for Anyone who wants to learn about AI or Technology enthusiasts who want to stay at the forefront of the latest AI developments or Artists and creatives looking to explore new dimensions of art with AI or Developers and designers who want to expand the possibilities of diffusion models.
Learn More About Diffusion Mastery: Flux, Stable Diffusion, Midjourney & more
What You Will Learn
- Introduction to Diffusion Models: Basics and first steps with diffusion models
- Prompt Engineering: Optimizing prompts for various platforms like DALL-E, MidJourney, Flux, and Stable Diffusion
- Stable Diffusion & Flux: Using open-source models, negative prompts, LoRAs for SDXL or Flux
- Guides for installing and using tools like Fooocus, ComfyUI, Forge, locally or in the cloud
- Flux: Usage for inpainting, IP Adapter, ControlNets, custom LoRAs, and more
- Training custom models & LoRAs, checkpoints, encoders, inpainting and upscaling, multiline prompts for creative image generation
- Creative Applications: Creating consistent characters, AI influencers, product placements, changing clothes and styles (e.g., anime)
- Specialized workflows and tools: Using tools like ComfyUI, Forge, Fooocus, integrating ControlNets, advanced prompting, and logo design
- Platforms: Utilizing Leonardo AI, MidJourney, Ideogram, Adobe Firefly, Google Colab, SeaArt, Replicate, and more
- Deepfakes: Faceswapping in photos and videos, installing programs for live deepfakes in Python, voice cloning, and legal concerns
- AI voices and music: Creating audiobooks, sound effects, and music with tools like Elevenlabs, Suno, Udio, and OpenAI API
- AI videos: Producing AI films with Hotshot, Kling AI, Runway, Pika, Dreammachine, Deforum, WrapFusion, Heygen, and more
- Upscaling and sound enhancement: Improving image, video, and sound quality, higher resolution, or converting to vector formats
- Ethics and security: Legal frameworks and data protection in the use of diffusion models
6. LLM Engineering: Master AI, Large Language Models & Agents
Instructor: Ligency Team
Become an LLM Engineer in 8 weeks: Build and deploy 8 LLM apps, mastering Generative AI and key theoretical concepts.
Course Highlights:
- Rating: 4.77 ⭐ (4256 reviews)
- Students Enrolled: 41697
- Course Length: 90998 hours
- Number of Lectures: 251
- Number of Quizzes: 0
LLM Engineering: Master AI, Large Language Models & Agents, has an average rating of 4.77, with 251 lectures, based on 4256 reviews, and has 41697 subscribers.
You will learn about Project 1: Make AI-powered brochure generator that scrapes and navigates company websites intelligently. Project 2: Build Multi-modal customer support agent for an airline with UI and function-calling. Project 3: Develop Tool that creates meeting minutes and action items from audio using both open- and closed-source models. Project 4: Make AI that converts Python code to optimized C++, boosting performance by 60,000x! Project 5: Build AI knowledge-worker using RAG to become an expert on all company-related matters. Project 6: Capstone Part A – Predict product prices from short descriptions using Frontier models. Project 7: Capstone Part B – Execute Fine-tuned open-source model to compete with Frontier in price prediction. Project 8: Capstone Part C – Build Autonomous multi agent system collaborating with models to spot deals and notify you of special bargains. Design and develop a full solution to a given business problem by selecting, training and applying LLMs Compare and contrast the latest techniques for improving the performance of your LLM solution, such as RAG, fine-tuning and agentic workflows Weigh up the leading 10 frontier and 10 open-source LLMs, and be able to select the best choice for a given task This course is ideal for individuals who are Aspiring AI engineers and data scientists eager to break into the field of Generative AI and LLMs. or Professionals looking to upskill and stay competitive in the rapidly evolving AI landscape. or Developers interested in building advanced AI applications with practical, hands-on experience. It is particularly useful for Aspiring AI engineers and data scientists eager to break into the field of Generative AI and LLMs. or Professionals looking to upskill and stay competitive in the rapidly evolving AI landscape. or Developers interested in building advanced AI applications with practical, hands-on experience.
Learn More About LLM Engineering: Master AI, Large Language Models & Agents
What You Will Learn
- Project 1: Make AI-powered brochure generator that scrapes and navigates company websites intelligently.
- Project 2: Build Multi-modal customer support agent for an airline with UI and function-calling.
- Project 3: Develop Tool that creates meeting minutes and action items from audio using both open- and closed-source models.
- Project 4: Make AI that converts Python code to optimized C++, boosting performance by 60,000x!
- Project 5: Build AI knowledge-worker using RAG to become an expert on all company-related matters.
- Project 6: Capstone Part A – Predict product prices from short descriptions using Frontier models.
- Project 7: Capstone Part B – Execute Fine-tuned open-source model to compete with Frontier in price prediction.
- Project 8: Capstone Part C – Build Autonomous multi agent system collaborating with models to spot deals and notify you of special bargains.
- Design and develop a full solution to a given business problem by selecting, training and applying LLMs
- Compare and contrast the latest techniques for improving the performance of your LLM solution, such as RAG, fine-tuning and agentic workflows
- Weigh up the leading 10 frontier and 10 open-source LLMs, and be able to select the best choice for a given task
5. The AI Engineer Course 2025: Complete AI Engineer Bootcamp
Instructor: 365 Careers
Complete AI Engineer Training: Python, NLP, Transformers, LLMs, LangChain, Hugging Face, APIs
Course Highlights:
- Rating: 4.6 ⭐ (1590 reviews)
- Students Enrolled: 15236
- Course Length: 87282 hours
- Number of Lectures: 367
- Number of Quizzes: 123
The AI Engineer Course 2025: Complete AI Engineer Bootcamp, has an average rating of 4.6, with 367 lectures, 123 quizzes, based on 1590 reviews, and has 15236 subscribers.
You will learn about The course provides the entire toolbox you need to become an AI Engineer Understand key Artificial Intelligence concepts and build a solid foundation Start coding in Python and learn how to use it for NLP and AI Impress interviewers by showing an understanding of the AI field Apply your skills to real-life business cases Harness the power of Large Language Models Leverage LangChain for seamless development of AI-driven applications by chaining interoperable components Become familiar with Hugging Face and the AI tools it offers Use APIs and connect to powerful foundation models Utilize Transformers for advanced speech-to-text This course is ideal for individuals who are You should take this course if you want to become an AI Engineer or if you want to learn about the field or This course is for you if you want a great career or The course is also ideal for beginners, as it starts from the fundamentals and gradually builds up your skills It is particularly useful for You should take this course if you want to become an AI Engineer or if you want to learn about the field or This course is for you if you want a great career or The course is also ideal for beginners, as it starts from the fundamentals and gradually builds up your skills.
Learn More About The AI Engineer Course 2025: Complete AI Engineer Bootcamp
What You Will Learn
- The course provides the entire toolbox you need to become an AI Engineer
- Understand key Artificial Intelligence concepts and build a solid foundation
- Start coding in Python and learn how to use it for NLP and AI
- Impress interviewers by showing an understanding of the AI field
- Apply your skills to real-life business cases
- Harness the power of Large Language Models
- Leverage LangChain for seamless development of AI-driven applications by chaining interoperable components
- Become familiar with Hugging Face and the AI tools it offers
- Use APIs and connect to powerful foundation models
- Utilize Transformers for advanced speech-to-text
4. All of AI: ChatGPT, Midjourney, Stable Diffusion & App Dev
Instructor: Arnold Oberleiter
ChatGPT, Prompt Engineering, OpenAI API, GPTs, Chatbots, Automation, AI-Apps, Generative AI, Machine Learning, Copilot
Course Highlights:
- Rating: 4.69 ⭐ (1629 reviews)
- Students Enrolled: 14821
- Course Length: 133319 hours
- Number of Lectures: 406
- Number of Quizzes: 0
All of AI: ChatGPT, Midjourney, Stable Diffusion & App Dev, has an average rating of 4.69, with 406 lectures, based on 1629 reviews, and has 14821 subscribers.
You will learn about Introduction to AI: What Artificial Intelligence Is and What It Is Not Detailed prompt engineering for Midjourney, ChatGPT, Dall-E, Stable Diffusion, Adobe Firefly and more Understanding Learning Methods: Machine Learning, Deep Learning, Neural Networks Examples of AI: FSD, LLMs, Voice Assistants, Diffusion Models, Deepfakes & More Fundamentals of ChatGPT The Basics of AI All Functions of ChatGPT The History of AI from DeepMind to AlphaGO by IBM How LLMs (Large Language Models) Work Using the OpenAI Playground Working with the OpenAI API and Assistant API How Diffusion Models Work Building Your Own GPTs Building Assistants with OpenAI Building Simple Apps with the OpenAI API Supervised Learning and Reinforcement Learning Speech and Image Recognition Everything About GPTs and the GPT Store Creating a Builder Profile and Earning Money with GPTs Generating Leads with GPTs Integrating Zapier Actions into GPTs Incorporating GPTs into Websites with Flowsie and Node JS Overview of Programming Languages, Libraries, and Development Tools Using Google Colab Exploring GitHub and Huggingface Details About LLMs: Parameters, Prompt Engineering, Multimodality GPT Vision Training Your Own Diffusion Models Fine-Tuning of Diffusion Models [Loras] with Colab and Dreambooth Everything About Loras and Models in Stable Diffusion Creating Your Own Face with Stable Diffusion Using Diffusion Models like Midjourney, Adobe Firefly, and Dall-E Fine-Tuning of LLMs [GPT] in Google Colab Text-to-Speech with Elevenlabs and Whisper Creating Music Videos with Deforum Social Media Videos with Wrapfusion and Kaiber Deepfakes with WAV2Lip and Voice Cloning AI Avatars with Midjourney, Elevenlabs, and D-ID Ethical Concerns, Copyright, Privacy Issues Create content faster than ever before through effective prompt techniques Opportunities and risks of AI/ML like ChatGPT AI Voice Tools: Easily create AI-generated speech for any use case and even clone your own voice completely AI Video Tools: Create video presentations and quickly produce social media content AI Photo Tools: Add movement to images, edit pictures using inpainting and outpainting Combine AI tools for the best results with Upscaling and more Learn, improve, and debug code programming Programming your own games Monetizing your AI skills and learn how to make Money with AI Side Hustle Ideas and how to Sell ChatBots Building a AI Automation Agency Boosting productivity in all areas of your life SEO optimization of your content All parameters and modifiers in Leonardo and Midjourney This course is ideal for individuals who are This course is aimed at everyone who is interested in using AI tools like ChatGPT, regardless of their background. or To everyone who wants to learn something new or To entrepreneurs who want to become more efficient and save money or Private individuals who are interested in AI and want to build their own models. It is particularly useful for This course is aimed at everyone who is interested in using AI tools like ChatGPT, regardless of their background. or To everyone who wants to learn something new or To entrepreneurs who want to become more efficient and save money or Private individuals who are interested in AI and want to build their own models.
Learn More About All of AI: ChatGPT, Midjourney, Stable Diffusion & App Dev
What You Will Learn
- Introduction to AI: What Artificial Intelligence Is and What It Is Not
- Detailed prompt engineering for Midjourney, ChatGPT, Dall-E, Stable Diffusion, Adobe Firefly and more
- Understanding Learning Methods: Machine Learning, Deep Learning, Neural Networks
- Examples of AI: FSD, LLMs, Voice Assistants, Diffusion Models, Deepfakes & More
- Fundamentals of ChatGPT
- The Basics of AI
- All Functions of ChatGPT
- The History of AI from DeepMind to AlphaGO by IBM
- How LLMs (Large Language Models) Work
- Using the OpenAI Playground
- Working with the OpenAI API and Assistant API
- How Diffusion Models Work
- Building Your Own GPTs
- Building Assistants with OpenAI
- Building Simple Apps with the OpenAI API
- Supervised Learning and Reinforcement Learning
- Speech and Image Recognition
- Everything About GPTs and the GPT Store
- Creating a Builder Profile and Earning Money with GPTs
- Generating Leads with GPTs
- Integrating Zapier Actions into GPTs
- Incorporating GPTs into Websites with Flowsie and Node JS
- Overview of Programming Languages, Libraries, and Development Tools
- Using Google Colab
- Exploring GitHub and Huggingface
- Details About LLMs: Parameters, Prompt Engineering, Multimodality
- GPT Vision
- Training Your Own Diffusion Models
- Fine-Tuning of Diffusion Models [Loras] with Colab and Dreambooth
- Everything About Loras and Models in Stable Diffusion
- Creating Your Own Face with Stable Diffusion
- Using Diffusion Models like Midjourney, Adobe Firefly, and Dall-E
- Fine-Tuning of LLMs [GPT] in Google Colab
- Text-to-Speech with Elevenlabs and Whisper
- Creating Music Videos with Deforum
- Social Media Videos with Wrapfusion and Kaiber
- Deepfakes with WAV2Lip and Voice Cloning
- AI Avatars with Midjourney, Elevenlabs, and D-ID
- Ethical Concerns, Copyright, Privacy Issues
- Create content faster than ever before through effective prompt techniques
- Opportunities and risks of AI/ML like ChatGPT
- AI Voice Tools: Easily create AI-generated speech for any use case and even clone your own voice completely
- AI Video Tools: Create video presentations and quickly produce social media content
- AI Photo Tools: Add movement to images, edit pictures using inpainting and outpainting
- Combine AI tools for the best results with Upscaling and more
- Learn, improve, and debug code programming
- Programming your own games
- Monetizing your AI skills and learn how to make Money with AI
- Side Hustle Ideas and how to Sell ChatBots
- Building a AI Automation Agency
- Boosting productivity in all areas of your life
- SEO optimization of your content
- All parameters and modifiers in Leonardo and Midjourney
3. AI Mastery Bootcamp: AI Algorithms, DeepSeek AI, AI Agents..
Instructor: Vivian Aranha
Complete AI Engineer Guide – AI Algorithms, AI Models like DeepSeek R1 AI, AI Agents, Python to Real-World AI Projects
Course Highlights:
- Rating: 4.57 ⭐ (97 reviews)
- Students Enrolled: 9237
- Course Length: 215575 hours
- Number of Lectures: 309
- Number of Quizzes: 1
AI Mastery Bootcamp: AI Algorithms, DeepSeek AI, AI Agents.., has an average rating of 4.57, with 309 lectures, 1 quizzes, based on 97 reviews, and has 9237 subscribers.
You will learn about Master Python for Artificial Intelligence: Write efficient Python code, essential for AI and ML programming tasks. Data Preprocessing Skills for Artificial Intelligence: Prepare, clean, and transform data to enhance model performance. Statistical Knowledge for Artificial Intelligence: Apply core statistics to understand data patterns and inform decisions. Build Machine Learning Models for Artificial Intelligence: Develop and fine-tune ML models for classification, regression, and clustering. Deep Learning Proficiency: Design and train neural networks, including CNNs and RNNs, for image and sequence tasks. Utilize Transfer Learning: Adapt pre-trained models to new tasks, saving time and resources. Deploy ML Models with APIs: Create scalable APIs to serve ML models in real-world applications. Containerize with Docker: Package models for portable deployment across environments. Monitor and Maintain Models: Track model performance, detect drift, and implement retraining pipelines. Complete ML Lifecycle: Master end-to-end AI project skills, from data to deployment and ongoing maintenance. This course is ideal for individuals who are Aspiring AI Engineers: Those looking to build a career in AI and gain hands-on, production-ready skills. or Data Scientists and Analysts: Professionals who want to expand their expertise to include machine learning, deep learning, and model deployment. or Software Engineers: Developers interested in applying programming skills to AI and machine learning projects. or Career Changers: Individuals from non-technical backgrounds with foundational Python knowledge, eager to transition into AI. or Graduate Students: Students in data science, computer science, or related fields wanting a practical, job-ready experience in AI engineering. or Tech Entrepreneurs: Founders and CTOs interested in understanding AI for building AI-driven products or managing AI teams. It is particularly useful for Aspiring AI Engineers: Those looking to build a career in AI and gain hands-on, production-ready skills. or Data Scientists and Analysts: Professionals who want to expand their expertise to include machine learning, deep learning, and model deployment. or Software Engineers: Developers interested in applying programming skills to AI and machine learning projects. or Career Changers: Individuals from non-technical backgrounds with foundational Python knowledge, eager to transition into AI. or Graduate Students: Students in data science, computer science, or related fields wanting a practical, job-ready experience in AI engineering. or Tech Entrepreneurs: Founders and CTOs interested in understanding AI for building AI-driven products or managing AI teams.
Learn More About AI Mastery Bootcamp: AI Algorithms, DeepSeek AI, AI Agents..
What You Will Learn
- Master Python for Artificial Intelligence: Write efficient Python code, essential for AI and ML programming tasks.
- Data Preprocessing Skills for Artificial Intelligence: Prepare, clean, and transform data to enhance model performance.
- Statistical Knowledge for Artificial Intelligence: Apply core statistics to understand data patterns and inform decisions.
- Build Machine Learning Models for Artificial Intelligence: Develop and fine-tune ML models for classification, regression, and clustering.
- Deep Learning Proficiency: Design and train neural networks, including CNNs and RNNs, for image and sequence tasks.
- Utilize Transfer Learning: Adapt pre-trained models to new tasks, saving time and resources.
- Deploy ML Models with APIs: Create scalable APIs to serve ML models in real-world applications.
- Containerize with Docker: Package models for portable deployment across environments.
- Monitor and Maintain Models: Track model performance, detect drift, and implement retraining pipelines.
- Complete ML Lifecycle: Master end-to-end AI project skills, from data to deployment and ongoing maintenance.
2. Ethical Generative AI: A Practical Guide for Professionals
Instructor: Dr. Seema Chokshi
Understand Generative AI, Navigate Ethical Issues, Apply Mitigation Techniques, and Implement Assessment Frameworks
Course Highlights:
- Rating: 5 ⭐ (7 reviews)
- Students Enrolled: 14
- Course Length: 4272 hours
- Number of Lectures: 13
- Number of Quizzes: 5
Ethical Generative AI: A Practical Guide for Professionals, has an average rating of 5, with 13 lectures, 5 quizzes, based on 7 reviews, and has 14 subscribers.
You will learn about Understand the fundamentals of Generative AI Models /tools Types of Ethical issues with Generative AI models/tools Learn to identify ethical issues when using Generative AI models/ tools Learn to successfully mitigate ethical issues when using Generative AI models/tools Learn the framework to assess the Ethical impact of an AI tool This course is ideal for individuals who are Business Professionals and leaders, Executives who want to become responsible users of Generative AI It is particularly useful for Business Professionals and leaders, Executives who want to become responsible users of Generative AI.
Learn More About Ethical Generative AI: A Practical Guide for Professionals
What You Will Learn
- Understand the fundamentals of Generative AI Models /tools
- Types of Ethical issues with Generative AI models/tools
- Learn to identify ethical issues when using Generative AI models/ tools
- Learn to successfully mitigate ethical issues when using Generative AI models/tools
- Learn the framework to assess the Ethical impact of an AI tool
1. Certified AI Compliance and Ethics Auditor (CACEA)
Instructor: YouAccel Training
Ensuring Ethical and Compliant AI: A Comprehensive Guide for Auditors
Course Highlights:
- Rating: 4.68 ⭐ (14 reviews)
- Students Enrolled: 1845
- Course Length: 65011 hours
- Number of Lectures: 182
- Number of Quizzes: 0
Certified AI Compliance and Ethics Auditor (CACEA), has an average rating of 4.68, with 182 lectures, based on 14 reviews, and has 1845 subscribers.
You will learn about Understand the vital role of an AI auditor in ensuring ethical practices. Learn core principles and objectives guiding AI audits. Explore fundamental AI and machine learning concepts. Study key differences between traditional and AI-driven systems. Identify and manage common risks in AI deployment. Grasp ethical principles such as fairness and non-discrimination. Gain insight into transparency and explainability requirements. Develop strategies for integrating AI governance with strategy. Familiarize with global and regional AI regulations. Understand the implications of non-compliance in AI. Master risk management frameworks for auditing AI systems. Plan and conduct comprehensive AI audits effectively. Document and report audit findings with clarity. Ensure data privacy and compliance with regulations. Evaluate AI transparency and explainability techniques. Identify and mitigate bias to achieve fair AI outcomes. This course is ideal for individuals who are Professionals aiming to understand AI ethics and compliance auditing. or Compliance officers seeking AI-specific regulatory knowledge. or Auditors transitioning to roles involving AI oversight. or Managers needing insights into AI governance structures. or Risk management experts focused on AI system evaluations. or Tech leaders integrating ethical practices in AI development. or Legal advisors specializing in AI regulations and compliance. It is particularly useful for Professionals aiming to understand AI ethics and compliance auditing. or Compliance officers seeking AI-specific regulatory knowledge. or Auditors transitioning to roles involving AI oversight. or Managers needing insights into AI governance structures. or Risk management experts focused on AI system evaluations. or Tech leaders integrating ethical practices in AI development. or Legal advisors specializing in AI regulations and compliance.
Learn More About Certified AI Compliance and Ethics Auditor (CACEA)
What You Will Learn
- Understand the vital role of an AI auditor in ensuring ethical practices.
- Learn core principles and objectives guiding AI audits.
- Explore fundamental AI and machine learning concepts.
- Study key differences between traditional and AI-driven systems.
- Identify and manage common risks in AI deployment.
- Grasp ethical principles such as fairness and non-discrimination.
- Gain insight into transparency and explainability requirements.
- Develop strategies for integrating AI governance with strategy.
- Familiarize with global and regional AI regulations.
- Understand the implications of non-compliance in AI.
- Master risk management frameworks for auditing AI systems.
- Plan and conduct comprehensive AI audits effectively.
- Document and report audit findings with clarity.
- Ensure data privacy and compliance with regulations.
- Evaluate AI transparency and explainability techniques.
- Identify and mitigate bias to achieve fair AI outcomes.
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