NumPy
NumPy is a beginner course on Python's core numerical computing library, built around fast array operations. Over 3 weeks, learners create and inspect arrays, use vectorized operations and masks, and summarize along an axis, then progress to broadcasting, aggregations, handling missing data, linear algebra, and performance-aware array code — suited to anyone new to NumPy.
Create and inspect arrays. Use vectorized operations and masks. Summarize along an axis.
What you'll learn
Course details
Duration
3 weeks
Best for
Anyone new to NumPy
This course is free
Course Curriculum
A module-by-module breakdown of what you'll cover in NumPy.
01Basic
4 topicsWeek 1
- What is NumPy, and why not just use Python lists?
- Creating arrays and understanding shape
- Indexing and slicing arrays
- Project: Analyze a small dataset with vectorized operations
02Intermediate
4 topicsWeek 2
- Broadcasting: operating on arrays of different shapes
- Aggregations: sum, mean, min, max, and the axis parameter
- Working with missing and invalid data: NaN
- Project: Clean and summarize a dataset with missing values
03Advanced
3 topicsWeek 2
- Arrays have shape and dtype
- Vectorized arithmetic and masks
- Views and copies affect later changes
04Pro
4 topicsWeek 3
- Performance: vectorization vs. loops, and memory layout
- Linear algebra with NumPy: dot products and matrix operations
- Random number generation and reproducibility
- Project: Simulate and analyze data with performance in mind
05AI Pro
3 topicsWeek 3
- Using AI tools (ChatGPT, Claude, Perplexity) to write and debug NumPy code faster
- Verifying AI-suggested NumPy code: check the numbers, not just that it runs
- Project: Use AI to vectorize a loop, then verify with a hand-calculated test case
Tools & Technologies
Hands-on practice with the same tools used by working professionals.
Communication & Soft Skills
Built into every course, alongside the technical curriculum.
Communication Skills
Practice explaining technical work clearly to teammates, managers, and clients.
Practical AI Skills
Hands-on training in using AI tools well — prompting, everyday workflows, and where AI actually helps versus where it doesn't.
Teamwork & Collaboration
Work in small project teams using real workflows like stand-ups and code reviews.
Problem Solving
Build the habit of breaking down ambiguous problems into clear, solvable steps.
Time Management
Learn to plan, prioritize, and deliver project work against realistic deadlines.
Presentation Skills
Present your project work and results with confidence, as you would to a client.
Resume & Profile Building
Build a strong resume, LinkedIn profile, and project portfolio that recruiters notice.
Interview Preparation
Mock interviews and portfolio reviews to get you ready for real job applications.
Career & Placement Support
100% of students enrolled in NumPy get full access to placement support — real tools and guidance, not just a promise. This is support and access, not a guaranteed job outcome.
Resume Builder
A resume auto-built from your real completed projects and certificates, ready to export.
Shareable Portfolio
A public portfolio page showcasing your approved projects, with a link you can share with employers.
Interview Preparation
Guidance on presenting your projects and experience clearly in real interviews.
Peer & Mentor Community
Ongoing access to our learner community for questions, feedback, and support after you finish.
What Your Certificates Look Like
Real, verifiable certificates with your name, NumPy, and a QR code anyone can scan to confirm they're genuine — one for completing the course, and a separate one if you take the internship track. Earning a certificate is free. To view, download and share it, there's a one-time ₹100 release fee per certificate — the same for free-course, paid-course and internship certificates.
Course Completion Certificate
Data24ZoneCertificate of Completion · Free Course
Illustrative recipient
Your Name Here
Example certificate for completion of
NumPy
- Certificate No.
- D24-SAMPLE
- Mode
- Self-Paced
- Duration
- 3 weeks
- Example issue date
- On completion
Sample only — not a real, issued certificate.
Verification is available only on issued certificates.
Internship Completion Certificate
Data24ZoneCertificate of Internship
Illustrative recipient
Your Name Here
Example certificate for completion of
NumPy
- Certificate No.
- D24-SAMPLE
- Mode
- Internship
- Duration
- 3 weeks
- Example issue date
- On completion
Sample only — not a real, issued certificate.
Verification is available only on issued certificates.
Frequently Asked Questions
What will I learn in the NumPy course?
You'll learn: Create and inspect arrays.; Use vectorized operations and masks.; Summarize along an axis..
What tools and technologies does the NumPy course cover?
This course covers: NumPy, Python, ChatGPT, Claude, Perplexity.
Is the NumPy course beginner-friendly?
Yes — this is a beginner-level course.
How long does the NumPy course take to complete?
The course is designed to be completed in approximately 3 weeks, depending on your pace.
What enrollment options are available for NumPy?
Project Training Track (₹1,499) — One defined learning project and 2 review sessions; no employment or stipend included. Self-Paced (₹1,999) — Learn anytime with the full recorded curriculum and community access.
Is there an internship option for NumPy?
Yes — the Internship track means working through real projects with our team and earning a separate Internship Certificate.
Will I get a certificate after completing NumPy?
Yes. Self-paced enrollment earns a course completion certificate once your final project is reviewed and approved. Internship enrollment earns an internship certificate once your internship projects are approved. Every certificate is publicly verifiable on our website and can be added directly to your LinkedIn profile. Earning it is free; releasing it to view, download and share is a one-time ₹100 fee per certificate.
Is placement support included with NumPy?
Yes — every enrolled student gets full access to our placement support: resume building, a shareable project portfolio, mock interview preparation, and guidance applying what you've built to real job applications. This is support and access, not a guaranteed job outcome — how quickly it leads to an offer depends on the market and your own effort.
