With over twelve years in Product Management and nine dedicated to artificial intelligence, my journey has spanned critical roles from leading product teams at Bloomberg to founding Welcome.AI. This experience has given me insights into the skills needed to understand AI's potential.
These courses are a practical list for anyone looking to learn about AI – whether you're a business professional, aspiring tech enthusiast, or curious learner.
1. AI for Everyone by DeepLearning.AI
Link: https://www.deeplearning.ai/courses/ai-for-everyone/
Duration: Approximately 2-3 hours
A non-technical course that transforms AI from an enigmatic technology to a strategic business tool. Professionals will:
- Decode AI's real-world capabilities and limitations
- Identify transformative AI opportunities within their organizations
- Understand the broader societal implications of artificial intelligence
- Develop a strategic framework for AI integration
Ideal for non-technical professionals who want to speak the language of AI without diving into complex technical details.
2. Introduction to Machine Learning in Production
Link: https://www.coursera.org/learn/introduction-to-machine-learning-in-production
Duration: Approximately 4-5 hours
This course provides a critical blueprint for understanding machine learning's operational mechanics. Key insights include:
- Comprehensive ML project lifecycle management
- Advanced deployment and monitoring strategies
- Performance optimization techniques
- Navigating complex data ecosystem challenges
Tip: Don't let technical complexity intimidate you. Focus on understanding core concepts that drive AI implementation.
3. Generative AI for Everyone
Link: https://www.deeplearning.ai/courses/generative-ai-for-everyone/ Duration: 3 hours
Led by AI luminary Andrew Ng, this course offers an unparalleled exploration of generative technologies:
- Deep dive into generative AI mechanics
- Real-world application case studies
- Strategic assessment of AI's transformative potential
- Ethical and business implications of emerging technologies
4. Google's Introduction to Generative AI Learning Path
Link: https://www.cloudskillsboost.google/paths/118
Duration: Can be completed over a weekend or in a single night
A comprehensive learning experience encompassing:
- Foundational large language model concepts
- Responsible AI development principles
- Practical generative AI implementation strategies
5. ChatGPT Prompt Engineering for Developers
Link: https://www.deeplearning.ai/short-courses/chatgpt-prompt-engineering-for-developers/
Duration: Approximately 1 hour
For professionals seeking to master AI interaction, this course provides:
- Advanced prompt engineering methodologies
- Custom chatbot development techniques
- Strategic approaches to leveraging Large Language Models
- Practical applications across summarization, inference, and content generation
Pro Tip: Backend prompting for engineering is similar to UI prompting – we often save prompts in databases to trigger specific tasks.
Strategic Perspective
These courses represent more than educational resources—they are strategic waypoints in understanding artificial intelligence's evolutionary trajectory. While they provide a comprehensive overview, true mastery emerges through continuous learning and practical application.
The next frontier lies in advanced model training and refinement—a journey that begins with foundational understanding.