How To Apply What You Learn

👋 Hey there !!

Welcome to Career Compass! In this week’s newsletter, I’ll cover:

🎯 Applying What You Learn

🎯 Best Practices On Project Documentation

🎯 Tips I Wish I Knew Earlier

Let’s get started!

Table of Contents

Read time: 5 minutes

🎯 Applying What You Learn

Do you need help applying what you learn through certifications? I’ve got your back.

Data Analytics certifications allow you to showcase skills for potential employers, provided you understand how to leverage them effectively, particularly during the studying process.

⁉️ How can we address this?

Here are some tips to improve your learning ⬇️

Approach certifications the right way

  1. Match the certification to your experience level If you already have some experience with data, there’s no point starting at the Foundation level, as it may even lower your initial commitment to finish it.

  2. Create a study schedule → Start small, with just 30 minutes. 30 minutes, 6 times a week, for 6 months is a total of 72 hours of study.

Pro-tip → If you spend a ratio of 1:3 between Theory Learning and Practice, you’ll end up practicing 54 hours of those 72. More on that in this post.

  1. Direct your practice → Work through sample datasets and case studies. Use public platforms to do a project that resonates with you. That way, you’ll know what to look for.

  2. Teach it to yourself. Explaining concepts to others is a great way to develop critical thinking, as it forces you to simplify things. But what if you don’t have anyone to chat with? Do it in front of the mirror. That simple.

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Create your study schedule using a platform like Notion.

Would you like to be featured in Career Compass? Submit your study schedule template, and I'll choose my favorite to showcase in a future newsletter

🎯 How to Document Your Data Analysis Projects

Documenting your data analytics projects is important for showcasing your work, collaborating with others, and impressing companies.

👨‍🏭 How can we address this?

Here are my top tips when documenting your projects ⬇️

  1. Use a clear project name

  2. Prepare it for both technical and non-technical users

  3. Provide a concise project description

  4. Include a table of contents or sections

  5. List the technologies and tools used to make the project

  6. Document your code with comments

  7. Discuss insights, conclusions, and future work

You should also be able to quickly update it without writing it all over again.

That’s why I built the Ultimate Data Portfolio → A one-stop shop for all your data projects. Feel free to check it out by clicking the button below.

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Create an outline system for your Data Projects, including sections like Project Summary, Project Scope & Data Sources.

🎯 Tips I Wish I Knew Earlier

Here’s what I wish I’d known when starting my career ⬇️

  1. Embrace the Learning Curve  Be curious, ask questions, and never stop learning.

  2. Communication is Key  Learn to turn complex insights into clear, concise messages.

  3. Seek Feedback → Use it to identify areas for improvement and refine your skill.

  4. Network Building a solid professional network can open new opportunities and collaborations.

  5. Stay Agile → Be prepared to adapt to new tools, technologies, and methodologies.

  6. Domain Knowledge Matters → A deep understanding of your industry can set you apart as a data analyst.

  7. Find Your Passion → Focus on areas that align with your interests and strengths.

  8. Stay Humble → No matter how skilled you become, there will always be more to learn.

Be like an octopus

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I’ve recently revamped my website. Feel free to check it out for more useful data resources.

Have you enjoyed this week’s newsletter? Forward it to a friend and have them sign up here.

👋 That’s it! Thank you!

See you next week.

Mo Chen

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