Hustle Hub #33

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Hey friends,

These 2 weeks have been quite crazy on my side with a new AI platform (limited beta) that I launched recently to help people get AI insights from data by simply asking questions (yes — just like ChatGPT).

Thanks to my early users, I received many insightful feedback and I’m currently working on improving the platform before launching it for public beta.

In today's issue, I’d like to share with you the 10 git commands every data scientist should know, why I say NO to stay focused, and a very insightful article on prompt engineering.

Let’s get to it! 🚀 

🛖 What's in the hub today?

• Tip: 10 Git commands every data scientist should know

• Mistake: I said YES too often

• Learning: Learn to say NO

• Article: Prompt Engineering

• Tool: Rows AI

Level Up Your Data Skills with Python 🚀

Finally, the wait is over. 🎉

Over the years, many people asked me if I still teach Python and data science. And the answer is YES!

This is my first online course (Intro to Python for Data Science) where I’m partnering with Rocket Academy to help you master the fundamentals of Python for data science. In just 2 days, you’ll learn Python from scratch and start analysing data with real-world datasets.

The course is designed to help you avoid all the mistakes I made when I first learned Python and 10x your speed to learn Python from scratch.

It’s a 2-day online workshop (Zoom) which will be held on 7-8 July. This is the first time (or might be the last time - depending on my schedule) I teach Python in public.

⭐️ 1 Tip

10 Git Commands Every Data Scientist Should Know

git remote -v

I often use this git command to check the remote repo that my project is pointing to so I know I am getting and updating code in the right remote repo.

🪵 You’ll use this git command when you want to:

• Identify remote repo: It shows the remote repo associated with a project, which is important for collaboration and sharing code with team members.

• Collaborate effectively: By knowing the remote repo, you can push your changes and pull updates from others, ensuring smooth collaboration.

git pull

I use this git command before I start working on my code to ensure I always have the updated code done by my teammates.

🪵 You’ll use this git command when you want to:

• Retrieve and incorporate the latest changes from a remote repo into your local repo.

• Avoid conflicts and ensure collaboration efficiency.

git checkout <your-branch-name>

I use this git command when I want to switch to another local branch to make changes to my code.

🪵 You’ll use this git command when you want to:

• Work on a specific branch, such as creating a new feature or fixing a bug, separate from the main branch.

• Prevent conflicts and work collaboratively with other team members.

git status

🪵 You’ll use this git command when you want to:

• Keep track of your changes and ensure that everything is in order before committing or pushing to the remote repo.

• Identify conflicts or differences in the repository state that need to be resolved.

git add .

🪵 You’ll use this git command when you want to:

• Add all the changes in the current directory and its subdirectories to the staging area.

git commit -m "your commit message"

🪵 You’ll use this git command when you want to:

• Keep track of the progress of your work and create a history of changes in the project.

• Provide a brief and meaningful commit message that describes the purpose or content of the commit.

git push

🪵 You’ll use this git command when you want to:

• Upload local commits and changes to a remote repo.

• Ensures that your changes are backed up remotely and can be accessed by others, promoting efficient collaboration and knowledge sharing.

git log

🪵 You’ll use this git command when you want to:

• Review the commit history, including the author, date, and commit messages.

• Track the progress of a project and understand the changes made over time.

git reset --hard

🪵 You’ll use this git command when you want to:

• Reset the state of your local repo to a specific commit, discarding any changes made after that commit.

• Want to completely remove or undo their local changes and revert to a previous commit.

git merge --abort

🪵 You’ll use this git command when you want to:

• Abort a merge operation that is in progress and return the repo to its previous state.

• Revert the merge and avoid incorrect or undesirable changes in the codebase.

⚠️ 1 Mistake

Recently I’m trying to do different things at the same time because I said YES to almost every opportunity.

While I’m grateful for the opportunities given, I slowly lost my focus on some projects that are truly important to me. Because of that, my limited time has been spread out to different commitments, distracting me from doing what truly matters in the long term.

🧠 1 Learning

I need to learn to say NO to the projects that are not important to me. A rule of thumb that I’m trying to follow when making a decision is this. For any project:

• If I’m not saying “HELL YES” at the very beginning, then I’ll default to saying “NO” to it.

• In short, if I spend my time considering if I should take a project, then by default I should say “NO” because this is not what I truly want.

I’m still testing out this approach, so I’ll report back to see how well it works for me sometime down the road.

🧠 Here’s what I’ve learned:

• I need to focus on 1-2 things that could give me the highest ROI.

• I need to know what to prioritise and remove other distractions.

📚️ 1 Article

Prompt Engineering (by Lilian Weng)

I read this article when I was learning more about prompt engineering. It was so insightful that I have to share it with you, especially when you’re building an LLM application.

📚️ Here are my takeaways from the article:

• Prompt engineering, also known as In-Context Prompting, involves methods for communicating with language models to guide their behaviour without updating model weights.

• Zero-shot and few-shot learning are two basic approaches used in prompt engineering for LLM models.

• The choice of prompt format, training examples, and their order can significantly impact model performance in in-context prompting.

• Instruction prompting and self-consistency sampling are techniques that can be used to improve model alignment and reasoning accuracy.

  Have you read this article? What's your thought on it?

🧰 1 Tool

Every week I filter all the AI tools that I’ve come across and share with you the AI tool that you can use for your data analytics (or data science) to hopefully improve your productivity. This week has no exception!

Rows AI is a platform where you can analyse your data in a spreadsheet format using AI — think of it like your personal Data Analyst! 🧠

All you need to do is simply ask questions and it can help you analyse, summarise, transform data, and generate insights. Quick a cool tool if you were to ask me.

🔥 Hustler Spotlight 🔥

👋🏻 How would you introduce yourself?

I’m an entrepreneur who loves to solve meaningful problems. Passionate about technology, AI, education, and fostering communities to address pressing global challenges and pave the way for a brighter future. Currently focused on global awareness about AI and harnessing its potential to create value for individuals and organizations.

👀 What’s your day to day like in your current role as a Founder & CEO at AI Planet?

My day typically begins with daily stand-up meetings with our product and business teams, with a focus on driving impact and creating value. A significant portion of my time is spent in meetings, understanding and addressing our new prospects and customers' needs with AI. Occasionally, I delve into administrative work, but my thoughts invariably gravitate towards product enhancement and problem-solving for meaningful impact. Although I enjoy hands-on tasks, time constraints and my team's expertise often relegate me to more strategic roles.

⭐️ What has been the biggest highlight of your career so far?

Without a doubt, founding and leading AI Planet has been the most rewarding aspect of my career. This journey has imparted invaluable lessons in resilience and perseverance, shaping my approach to failures and reinforcing the importance of tenacity.

The most gratifying part lies in the profound impact we've been able to make by empowering thousands of individuals and companies with AI education and solutions. This contribution continues to fuel our collective passion and commitment at AI Planet.

🚀 What's a data or AI trend you're watching this year?

The spotlight is on Generative AI currently. It's fascinating to witness its diverse applications. Everyone is fascinated by it and curious to know what it can do for them, their role and their business. There is a bit of fear, there is a bit of hope.

In parallel, the infrastructure (MLOps) to support and reliably scale these Generative AI models is going to be a crucial area of focus.

💼 What advice would you give someone starting out in Data Science?

Beginning your journey in Data Science requires a solid foundation of the fundamentals. Instead of worrying about which programming language or algorithm to choose, concentrate on intuitively understanding the underlying principles. Remember, Data Science is all about using data in a scientific way to make informed decisions. The choice of languages or frameworks is just a means or tool to achieve that purpose.

Also, prioritize problem-solving and don't be discouraged by obstacles in comprehending new concepts. We're fortunate to have access to innovative tools like Generative AI, ChatGPT, and AI Planet's Jupiter, which simplify and personalize learning. For instance, you can choose to learn concepts through the lens of your role models or interests. If you're a Messi fan and wish to understand the concept of Pi, these tools can explain it using a Messi-themed narrative or in a simple way a 5-year-old would understand. This makes learning more engaging, fun and relatable. Make the most of the tools to solidify your concepts!

🤯 What’s the most important career lesson you wish you’d learned earlier?

The essence of entrepreneurship is to commence as early as possible. It's never too early or never too late to forge your path and create something of your own. There will be ups and downs, you learn by making mistakes, and gradually you start celebrating them as much as you celebrate success.

🧠 How would you learn Data Science if you had to start over?

I would take advantage of ChatGPT or AI Planet’s Jupiter to streamline the learning process and solidify my concepts. I believe consistency in personalization and simplification were missing in education earlier, but with Generative AI this is not a problem. Furthermore, I'd dedicate more time to problem-solving, which provides good hands-on experience and allows you to work on problems that are of your passion.

🔥 Where can we find your amazing work?

You can explore:

• https://aiplanet.com/

• https://aiplanet.com/apps

• https://app.aimarketplace.co/

📚 What's your favorite book?

While I'm not an ardent reader of books, I consume a substantial amount of information from blogs, research papers, and documentaries. However, one book I do appreciate is Walter Isaacson's biography of Steve Jobs.

🚀 Whenever you’re ready, there are 4 ways I can help you:

1. Book a coaching call with me if you need help in the following:

2. Promote your brand to 1,000+ subscribers in the data/tech space by sponsoring this newsletter.

3. Watch my YouTube videos where I talk about data science tips, programming, and my tech life (P.S. Don’t forget to like and subscribe 💜).

4. Follow me on LinkedIn and Twitter for more data science career insights, my mistakes and lessons learned from building a startup.

That's all for today

Thanks for reading. I hope you enjoyed today's issue. More than that, I hope it has helped you in some ways and brought you some peace of mind.

You can always write to me by simply replying to this newsletter and we can chat.

See you again next week.

- Admond