Getting Started with Data Analysis Using Python 2
Data literacy is now table stakes—whether you’re pivoting into analytics or strengthening your technical foundation. This course cuts through the noise and teaches you Python’s core data analysis tools in under 2.5 hours, with real sandboxes to practise immediately.
AIU.ac Verdict: Ideal for career-switchers and junior analysts who need working Python skills fast, without the fluff. The hands-on labs are genuinely useful, though you’ll need follow-up courses to tackle complex statistical modelling or large-scale pipelines.
What This Course Covers
You’ll work through Python’s essential data analysis libraries—pandas, NumPy, and Matplotlib—learning how to load datasets, perform basic transformations, and create meaningful visualisations. The course emphasises practical workflows: reading CSV files, filtering rows, calculating summary statistics, and spotting trends visually. Each concept includes a sandbox environment where you write actual code, not just watch demos.
Terry Toy structures the material around real-world scenarios: cleaning messy data, answering business questions with aggregations, and communicating findings through charts. By the end, you’ll confidently move from raw data to actionable insights using Python—the exact skill set employers want in analytics-adjacent roles.
Who Is This Course For?
Ideal for:
- Career-switchers into data roles: Need foundational Python skills without a 6-month bootcamp commitment. This 2.5-hour sprint covers what you’ll use on day one.
- Business analysts upskilling technically: Already understand data problems; now you need the Python toolkit to explore datasets independently instead of waiting for engineers.
- Students or graduates entering tech: Building a portfolio or preparing for junior analyst interviews. Hands-on labs give you real code samples to discuss.
May not suit:
- Experienced data scientists: You’ll find this too introductory. Jump straight to advanced Pluralsight courses on machine learning or statistical modelling.
- Non-technical professionals without coding exposure: Assumes basic programming familiarity. If you’ve never written code, start with a Python fundamentals course first.
Frequently Asked Questions
How long does Getting Started with Data Analysis Using Python 2 take?
2 hours 23 minutes of video content. Most learners complete it in one sitting or spread across 2–3 focused sessions.
Do I need prior Python experience?
Basic familiarity with Python syntax helps, but the course assumes you understand variables, loops, and functions. If you’re brand new to Python, take a foundational course first.
Are there hands-on labs or just videos?
Both. Pluralsight’s sandbox environments let you write and run Python code directly in your browser—no local setup required.
Will this prepare me for a data analyst role?
It’s a strong foundation. You’ll know pandas, NumPy, and Matplotlib inside out. For junior analyst interviews, pair this with SQL and domain knowledge of your target industry.
Course by Terry Toy on Pluralsight. Duration: 2h 23m. Last verified by AIU.ac: March 2026.
