Data Science Fundamentals with Python — PickAClass
⏱ 2h 30m 📚 25 lessons 🎧 Audio version

Data Science Fundamentals with Python

Acquire the essential programming, statistical, and machine learning skills needed to start your journey in data science.

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  • 🌐 In English
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About this course

Are you ready to unlock the power of data and embark on a rewarding career in data science? This course provides the essential building blocks you need to understand, analyze, and interpret complex datasets. By the end of this program, you will possess a solid understanding of data science principles and practical skills in Python, enabling you to confidently tackle real-world data challenges and prepare for further specialization. What you'll learn: * Understand foundational statistical concepts and their application in data analysis. * Learn to program effectively in Python for data manipulation using libraries like Pandas and NumPy. * Apply essential data cleaning, exploration, and visualization techniques to uncover insights. * Grasp the core principles of machine learning, including supervised and unsupervised algorithms. * Practice building and evaluating simple predictive models. * Develop robust data workflows, including basic data validation and testing practices for maintainable code. The course begins with an introduction to key data science terminology and setting up your development environment. You will then progress through foundational programming concepts in Python, statistical analysis, data manipulation, and an introduction to machine learning algorithms, culminating in practical application through exercises. This course is designed for absolute beginners with no prior experience in programming or data science. All concepts are explained clearly from the ground up. Start your journey into the exciting world of data science today.

What you'll get

  • 📜 Certificate of completion
    Add it to your LinkedIn profile
  • 💬 Personal AI tutor
    Stuck on a lesson? Ask your built-in tutor anything, any time.
  • 🎧 Audio version included
    Learn on the go — no screen needed
  • ♾️ Lifetime access
    Come back anytime, no expiry
  • 📱 Phone or computer
    Works anywhere, any device
  • 💸 14-day refund
    No questions asked
  • Short & focused
    2h 30m of practical content

Certificate of completion

Every course you complete on PickAClass issues a credential like this — original, with its own code, verifiable by URL, and detailed about what was actually demonstrated.

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PickAClass
Skills profile · verifiable
Document
Certificate of Mastery
This certifies that
Name Surname
has successfully demonstrated mastery of
Data Science Fundamentals with Python
Skills demonstrated
Behavioral pattern analysis
Foundational
1.2 hrs
Decision-architecture frameworks
Proficient
1.4 hrs
A/B test design
Proficient
1.7 hrs
Behavioral copywriting
Advanced
1.9 hrs
P
PickAClass — Name Surname
Data Science Fundamentals with Python
Page 2 of 2
Performance detail
Coursework summary
Lessons completed 14 / 14
Practice questions 26 / 28
Assignments submitted 4 (avg 4.5 / 5)
Capstone project Reviewed — 4.6 / 5
Total practice 6.2 hrs
Performance benchmark
Cohort rank Top 12% of 1,625
Time to completion 11 days (median: 22)
Mastery score 91 / 100
Practice-question score 94%
Skill verification Verified Skill Path
Verify this credential
pickaclass.com/certificates/PCC-2026-X4F7-AP19
Issued under the academic standards of PickAClass. Skill levels reflect assessed performance against the course's competency rubric. This is an original credential of this platform.

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Frequently asked

What do I need to take this course? +

Just a phone or computer with internet. No installs, no special hardware.

How do I pay? +

By card via Stripe. We don’t store card details — Stripe handles them securely.

Can I get a refund? +

Yes — full refund within 14 days, no questions asked.

How long will I have access? +

Forever. Once you purchase, the course is yours to revisit anytime.

Will I get a certificate? +

Yes. On completion you'll receive a certificate you can add to your LinkedIn profile.

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