Apache Spark & PySpark
Apache Spark & PySpark is an intermediate, 8-week course for learners who already know Python, SQL and data-pipeline fundamentals. It teaches building PySpark transformations with explicit schemas, correct join semantics, partition awareness, and measurable execution behavior using the Spark UI, culminating in an event aggregation pipeline project with plan inspection and skew analysis.
Build PySpark transformations with correct schema, join semantics, partition awareness and measurable execution behavior.
What you'll learn
Course details
Duration
8 weeks
Best for
Learners who already have: Python, SQL and data-pipeline fundamentals.
Enrollment isn't open for this course yet — check back soon or contact us.
Course Curriculum
A module-by-module breakdown of what you'll cover in Apache Spark & PySpark.
01Basic
4 topicsWeeks 1–2
- What is Apache Spark, and why not just use Pandas?
- DataFrames, schemas, and basic transformations
- Lazy evaluation: transformations vs. actions
- Project: Build and analyze a PySpark transformation pipeline
02Intermediate
4 topicsWeek 3
- Joins in Spark: types, broadcast joins, and skew
- Partitioning: how Spark distributes data across workers
- Caching and persisting: reusing intermediate results
- Project: Optimize a join-heavy pipeline
03Advanced
4 topicsWeeks 4–5
- Validate data before trusting the report
- Build a repeatable pipeline with explicit boundaries
- Use explicit schemas and native expressions
- Inspect join cardinality and skew before tuning
04Pro
4 topicsWeek 6
- Reading the Spark UI: diagnosing real performance problems
- User-Defined Functions (UDFs) and their performance cost
- Structured Streaming: processing data as it arrives
- Project: Diagnose and optimize a slow Spark pipeline
05AI Pro
3 topicsWeeks 7–8
- Using Claude, ChatGPT, and Perplexity to write and optimize PySpark code
- Verifying AI-suggested Spark optimizations with .explain() and the Spark UI
- Project: Use AI to replace a UDF, then verify correctness and speed
Tools & Technologies
Hands-on practice with the same tools used by working professionals.
Part of a bigger program
This skill is one of the real building blocks inside our Career Program— worth a look if you want the fuller, job-ready path instead of just this one piece.
Real-Time, Industry-Based Projects
This is project-based learning modeled on real industry scenarios — you'll build portfolio-ready work as you go, not just watch lectures.
Every course includes a guided internship on top of your project work — so you graduate with real experience, not just a certificate.
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 Apache Spark & PySpark 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, Apache Spark & PySpark, 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
Illustrative recipient
Your Name Here
Example certificate for completion of
Apache Spark & PySpark
- Certificate No.
- D24-SAMPLE
- Mode
- Self-Paced
- Duration
- 8 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
Apache Spark & PySpark
- Certificate No.
- D24-SAMPLE
- Mode
- Internship
- Duration
- 8 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 Apache Spark & PySpark course?
You'll learn: Validate data before trusting the report; Build a repeatable pipeline with explicit boundaries; Use explicit schemas and native expressions; Inspect join cardinality and skew before tuning.
What tools and technologies does the Apache Spark & PySpark course cover?
This course covers: Apache Spark, PySpark, Python, ChatGPT, Claude, Perplexity.
Is the Apache Spark & PySpark course beginner-friendly?
This is a intermediate-level course, so it assumes some prior familiarity with the subject.
How long does the Apache Spark & PySpark course take to complete?
The course is designed to be completed in approximately 8 weeks, depending on your pace.
What enrollment options are available for Apache Spark & PySpark?
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 Apache Spark & PySpark?
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 Apache Spark & PySpark?
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.
What kind of projects will I build in Apache Spark & PySpark?
You'll work on real projects such as: Event aggregation pipeline with plan inspection and skew analysis.
Is placement support included with Apache Spark & PySpark?
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.
