Python Programming with NumPy, Pandas, and Regular Expressions — PickAClass
⏱ 2h 30m 📚 25 lessons 🎧 Audio version

Python Programming with NumPy, Pandas, and Regular Expressions

Learn core Python syntax and master essential data libraries like NumPy, Pandas, and regular expressions to start your journey in programming and data analysis.

  • 💬 AI instructor
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  • 🕐 Start anytime
    No schedules or deadlines — learn at your own pace, whenever suits you.
  • 🌐 In English
    Lessons, tasks and certificate — all fully in your language.

About this course

Python is the world's most popular programming language, but learning its syntax is only the first step. To write real-world applications and work with data, you need to understand its core libraries. This text-based course guides you from absolute beginner to writing clean, functional Python code. You will build a solid foundation in Python syntax, learn to manipulate text with regular expressions, and start analyzing data using NumPy and Pandas. What you'll learn: - Learn fundamental Python syntax, including variables, loops, and control flow. - Understand modern Python practices like type hints and virtual environments. - Apply regular expressions using the re library to parse and clean text data. - Master NumPy arrays for efficient numerical computing and mathematical operations. - Practice data manipulation and analysis using Pandas DataFrames. - Create clean, readable code by following modern PEP 8 formatting standards. You will start with key terminology and basic programming concepts before moving on to reading and analyzing code snippets that teach you how to process text and manipulate datasets. This course is designed for absolute beginners with no prior programming experience. Start reading today to build your Python programming foundation.

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
Python Programming with NumPy, Pandas, and Regular Expressions
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
Python Programming with NumPy, Pandas, and Regular Expressions
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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