Lead the GenAI revolution. Future-proof your skills by understanding AI basics, machine learning, algorithms, ethical practices, and real-world applications. Stay ahead in tech leadership.

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Whether you’re leading a team on creating AI solutions, or you just want a better understanding of AI, then this course is for you. In this course, I have deconstructed the concepts most relevant for you.
 
You will start by learning the basics of AI, its connection with machine learning, and the different types of algorithms you should be familiar with. You’ll then learn the rules, best practices, and infrastructure for creating great AI products that users trust. Then, you will go through some real case studies of AI application and do a deep dive into Ethical AI. You'll end by getting an outlook into the current status and future of AI. In a nutshell, this course is your no-fuss, comprehensive guide to the essentials of AI.

Grokking AI for Engineering & Product Managers

### Further readings

We have now covered the main aspects of responsible AI. I highly recommend that you dive deeper into these topics. So, I am going to suggest some further reading material here. 

Big companies like Microsoft and Google have been putting a lot of brainpower to tackle these issues, and as leaders in the AI space, they have created guidelines to help organizations create responsible AI solutions. As per Sundar Pichai, Google and Alphabet CEO:

*“Companies such as ours cannot just build promising new technology and let market forces decide how it will be used. It is equally incumbent on us to make sure that technology is harnessed for good and available to everyone.”*

 
- [Microsoft AI principles](https://www.microsoft.com/en-us/ai/our-approach-to-ai)

- [Responsible bots: 10 guidelines for developers of conversational AI, Microsoft](
https://www.microsoft.com/en-us/research/uploads/prod/2018/11/Bot_Guidelines_Nov_2018.pdf)

- [AI at Google: our principles](https://www.blog.google/technology/ai/ai-principles/)

- [Responsible AI Practices, Google](https://ai.google/responsibilities/responsible-ai-practices/?category=fairness)

<br><br>

### Recap
As a section recap, I am going to leave you with this very nice table from McKinsey:

# Further readings

We have now covered the main aspects of responsible AI. I highly recommend that you dive deeper into these topics. So, I am going to suggest some further reading material here. 

Big companies like Microsoft and Google have been putting a lot of brainpower to tackle these issues, and as leaders in the AI space, they have created guidelines to help organizations create responsible AI solutions. As per Sundar Pichai, Google and Alphabet CEO:

*“Companies such as ours cannot just build promising new technology and let market forces decide how it will be used. It is equally incumbent on us to make sure that technology is harnessed for good and available to everyone.”*

 
- [Microsoft AI principles](https://www.microsoft.com/en-us/ai/our-approach-to-ai)

- [Responsible bots: 10 guidelines for developers of conversational AI, Microsoft](
https://www.microsoft.com/en-us/research/uploads/prod/2018/11/Bot_Guidelines_Nov_2018.pdf)

- [AI at Google: our principles](https://www.blog.google/technology/ai/ai-principles/)

- [Responsible AI Practices, Google](https://ai.google/responsibilities/responsible-ai-practices/?category=fairness)

<br><br>

# Recap
As a section recap, I am going to leave you with this very nice table from McKinsey:

This lesson wraps up the chapter about responsible AI by providing some further readings. 

The Fundamentals

AI in Practice

Real Case Studies

Responsible AI

What's Next

Responsible AI Practices: Addendum

Further readings

Recap