<ul data-eligibleForWebStory="true"><li>The individual tried learning data science in 30 days through YouTube tutorials and free courses, but found the random approach led to burnout.</li><li>They discovered the importance of following a structured learning path, focusing on Python basics, statistics, data visualization, and simple machine learning.</li><li>Building a mini project analyzing COVID data using pandas and Seaborn helped in understanding concepts better through practical application.</li><li>Key takeaways included daily focused learning, hands-on projects, following one structured roadmap, and tracking progress, emphasizing the need to avoid jumping between multiple courses and obsessing over tools.</li></ul>

Tried Learning Data Science in 30 Days — Here’s What Actually Worked"

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