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FAQ
Frequently asked questions
Yes — the tutorials, blogs, interview questions and the online compiler are free, and no account is required to read or run code.
PySpark is the Python API for Apache Spark, used for large-scale data processing, analytics and machine learning. It is one of the most in-demand skills in data engineering.
Basic Python helps but is not required. The learning paths start from fundamentals and are sequenced so each stage states what it assumes.
Yes. There is a free PySpark and Python compiler at pyspark.in/pyspark-compiler. You can write and run code in the browser with no local Spark, Java or Python setup.
Apache Spark, PySpark, Python, SQL, Machine Learning, Deep Learning, NLP, Generative AI and AI Agents, alongside data engineering pipeline and platform topics.
The interview section groups questions by topic and by company, with worked explanations and runnable examples. There are also mock interview rounds and an interview simulator.
Yes. Content is written by practitioners with industry experience in data engineering, machine learning and AI delivery.
Yes. Project tracks cover end-to-end builds such as ETL pipelines and log analysis, each ending with something you can put in a repository.
You can connect through LinkedIn and X, or email the team directly to hear about community opportunities.
Certifications are available from the certifications page. Email pysparkteam@gmail.com if you need details on a specific assessment or programme format.