95.8/100: What My First Semester in Data Science Actually Looked Like

2026-04-23 · Source: Machine Learning on Medium · Field: Technology & Digital — Data Science & Analytics, Artificial Intelligence & Machine Learning · Depth: Novice, short

Summary

An executive assistant and videographer, also tutoring five evenings a week, achieved a 95.8/100 score in her first data science semester at AltSchool. The curriculum covered Python functions, data sourcing, Pandas, DataFrames, data cleaning, handling missing values, grouping, aggregation, and outlier detection. Despite a demanding schedule with no large study blocks, she successfully integrated learning into her daily life. Her study methods included writing notes after each live class, solving practice questions repeatedly for difficult concepts, and using AI tools as a support system rather than a shortcut. She independently completed a data science project on a sleep and lifestyle dataset, earning 29/30 marks, and is now pursuing Semester 2 with increased confidence.

Key takeaway

For data science students balancing demanding schedules, prioritize active learning methods like writing notes and solving practice problems over passive review. Integrate AI tools as a supplementary aid for understanding, but ensure you maintain ownership of the problem-solving process. Your commitment to consistent, focused effort in available time gaps will be more impactful than seeking large, uninterrupted study blocks.

Key insights

Consistent application and strategic learning methods enable success in data science despite a busy schedule.

Principles

• Active recall beats passive review.
• AI is a tool, not a replacement for understanding.

Method

Study by writing key takeaways, solving practice problems for difficult concepts, and using AI for explanations, not shortcuts. Trust instructor guidelines for projects.

In practice

• Write notes after every learning session.
• Solve practice questions repeatedly.
• Use AI for concept clarification.

Topics

• Data Science Education
• Python Programming
• Pandas Library
• Data Wrangling
• Outlier Detection

Code references

• FisayoSangolade/HealthySleepAnalysis

Best for: AI Student, Data Scientist

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Editorial summary, takeaway, and curation by AIssential. Original article published by Machine Learning on Medium.