Data Science Roadmap 2024 | Data Science Weekly Study Plan | Free Resources to Become Data Scientist

Summary

This video offers an in-depth data science study plan spanning six months, requiring a daily four-hour commitment. It emphasizes the importance of both tool skills, like Python and SQL, and core skills, including statistics and presentation. The presenter, an experienced data scientist, warns against industry scams and clickbait, advocating for real industry knowledge. The plan includes weekly goals, project work, and building a strong LinkedIn profile for professional visibility. It concludes with advice on learning efficiently and building a professional network for career advancement.

Takeaways

• 📈 The data science roadmap requires a commitment of 4 hours of study daily for 6 months, emphasizing that there are no shortcuts to learning.
• 💼 The speaker's credibility is established through his experience at Bloomberg USA and his role in data scientist interviews at his company, ATCK Technologies.
• 🔧 A balance of tool skills and core skills is necessary for a data scientist, with the roadmap suggesting a 3:1 study time allocation respectively.
• 🧐 Week zero is dedicated to research and self-protection from scams in the ad tech industry, particularly job guarantee programs that promise quick results.
• 🐍 Python is a foundational tool for data scientists, with the first two weeks focused on learning its fundamental concepts through a free playlist.
• 🔗 Building a strong LinkedIn profile is crucial, with a provided checklist to enhance professional online presence.
• 💡 The importance of engaging with the data science community on LinkedIn is highlighted, suggesting following influential figures and participating in discussions.
• 📊 Emphasis on learning libraries like NumPy, pandas, Matplotlib, and seaborn for data manipulation and analysis.
• 📈 The roadmap includes a week dedicated to exploratory data analysis, combining tool skills with mathematical and statistical knowledge.
• 📊 SQL is a key skill for data scientists, with resources provided to learn basic to advanced queries, emphasizing its importance in data retrieval.
• 💬 The speaker stresses the need for soft skills like presentation and communication, which are essential for effectively sharing data insights with stakeholders.

Q & A

What is the recommended daily study time for the data science roadmap mentioned in the script?

The recommended daily study time is 4 hours, with a focus on tool skills for 3 hours and core skills for 1 hour.

How long is the data science roadmap designed to take?

The data science roadmap is designed to take 6 months to complete.

What is the importance of researching and protecting oneself from scams in the ad tech industry as discussed in the script?

The script emphasizes the importance of researching and protecting oneself from scams in the ad tech industry to avoid falling for false promises of quick learning or job guarantees, which are often used to increase revenues by making deceptive claims.

Why is building a strong LinkedIn profile considered a core skill in the data science roadmap?

A strong LinkedIn profile is considered a core skill because it helps in showcasing one's work to the world, which can lead to interview calls and job opportunities in data science.

What are the three Python libraries that data scientists commonly use for data analysis as mentioned in the script?

The three Python libraries that data scientists commonly use for data analysis are pandas, matplotlib, and seaborn.

How does the script suggest one should engage with LinkedIn posts to build a professional network?

The script suggests engaging with LinkedIn posts by making meaningful comments, not generic ones, to build a positive impression and potentially connect with data science managers or professionals in the industry.

What is the significance of learning math and statistics in the data science roadmap?

Math and statistics are significant in the data science roadmap because they form the foundational concepts behind data science, and unlike frameworks that may change, the mathematical and statistical principles remain constant.

Why is it recommended to participate in SQL project challenges as part of the data science roadmap?

Participating in SQL project challenges helps in practicing SQL skills, generating insights, and presenting them effectively, which can be showcased on LinkedIn to demonstrate one's abilities to potential employers.

What is the purpose of learning project management techniques like scrum and kanban in the data science roadmap?

Learning project management techniques like scrum and kanban is important for data scientists as they help in executing data science projects efficiently and effectively.

How does the script advise on building a professional presence on LinkedIn for data scientists?

The script advises building a professional presence on LinkedIn by engaging with industry influencers, making meaningful comments, connecting with professionals, and showcasing one's work and insights through posts.

What are the key assignments for someone following the data science roadmap in the first three weeks?

The key assignments for the first three weeks include finishing exercises from the provided Python playlist, creating a professional LinkedIn profile, and writing meaningful comments on LinkedIn posts.