Python Full Stack Computational Finance Framework Interview

Name: Python Full Stack Computational Finance Framework Interview
Rating: 4.5 (13 reviews)

Interview Prep: Python Full Stack Computational Framework: Solving Tickets for Real life Job Like scenarios with Tickets

Created byShivgan Joshi, abhi verma, Prakash Chandr Nandanwar

Last updated 6/2025

English

What you'll learn

Python 101 for Begineers for Full Stack Computational
Learning how to use backend and frontend testing
Learn how to solve tickets and assignments for real job
Developing code for Computational Frameworks on Large Data

Course content

4 sections • 36 lectures • 48m total length

Introduction to the Content of the Course and all Terms0:08
Intro to Content1:09
Master the full stack compute framework, including tasks, workflows, Jenkins build, and local testing, and practice solving real work tickets to start contributing immediately.
Intro to Full Stack compute platform0:09
Intro to Full Stack Compute Platform Video1:55
Explain how a full stack compute platform translates notebook logic into backend tasks and workflows, then renders results on the UI while incorporating DevOps, big data, and pipelines.
Intro to Tasks0:18
Intro to task - video1:22
Intro to Workflows0:21
Intro to workflows - video1:31
Learn how workflows power the front end by displaying names and descriptions, connect the UI to back-end tasks, manage input, execution, and complementary workflows, and perform integrity testing.
Intro to Notemaking0:08
Checkpoint - Tasks
Checkpoint - Workflows
Intro to notemaking - video0:55
Learn to create detailed, day-by-day notes on Wikipedia for each ticket, including workflow names, version builds, repo and Jenkins links, UI and Jenkins screenshots, error messages, and structured headings.
Intro to User Account Env Variables in Windows0:19
Intro to venv, env variables and cache1:15
Set up and manage a virtual environment, environment variables, and cache to ensure reliable local unit tests. Follow project-specific setup steps, including setup.py and make commands, for PySpark testing.
Checkpont Note Making
Checkpont - setup for local testing / Venv / debugging
Intro to ODBC Connections0:10

Batch runs3:37
Reading notes from wikipedia, emails, shared drive, videos carefully is the most imp job other runs at alpha beta gamma farmworks, older un on our own framework, this 90% of the job?
Input csv for the bath to get diff port and market projections? Yes
Running multiple runs using csv? Yes
Batch runs for input to start with? Yes
Holding batch run and also Unemployment batch runs
Views vs table creation - temp vs permanent table creation has to be checked as the order of how we run the batch and any manual run might be custom? Yes
At the end do the runs
Code for batch running
Batch runs

Introduction to Assignments and Tickets0:05
Intro to Tickets and Assignments - video0:50
Intro to Code Change Request0:10
Code change request steps - video0:30
18 Sample Tickets0:05
Ticket: Rename task workflows and name on the front end0:16
Ticket: Observing build and if fails at deploy change table1:11
Observe the build to locate failures, especially at the deploy step, and adjust the table version when needed; restart and test locally for workflow integrity, registration integrity, and schema issues.
Ticket Making unit test work locally - Correct setup venv2:00
Make tests pass locally by setting up the correct virtual environment with the prescribed make/build/setup.py steps, clearing cache, and validating non-pyspark tests before spark tests.
Ticket (advanced) Ref workflows1:16
Master advanced reference workflows by using the ref command to connect input and execution workflows, test locally, run spark jobs, and pull access date and names from references.
Ticket: Rename task workflows and name on the front end - video3:07
Rename task workflows on the front end, adjust unit test and axis names, then run workflow registration integrity tests, the Jenkins build, and front-end checks of input, execution, and output.
Ticket Handle Date time Column - str to date time to string2:09
Handle date time columns across Pandas and Spark by normalizing strings, dash and slash formats, and schemas, then reliably join data frames with Spark and use notebooks for schema checks.
Ticket - Master Simulation Run1:19
Master the master simulation run by selecting default options to ensure minimal input and configuration of market and unemployment files. Keep time steps minimized for a quick, working simulation.
Ticket: Running the ui frontend1:46
Run the UI frontend to verify access, ensure upload and execution steps align on version and file name, and anticipate failures from schemas, typos, and data references.
Ticket: Run In house spark df comparison0:07
Ticket Comparing runs and results from different repos0:18
Ticket Address comments on Pull Request1:29
Ticket Version upgrades for full stack framework0:07
Ticket: Changing unit tests as needed (after change of a logic in task -1 line1:43
After any logic change, update the unit test by regenerating the expected output from CSV data. Verify the virtual environment and run non-spark tests before schema changes.
All 18 tickets in one video8:58
This video reviews all 18 tickets, showing renaming workflows and tasks, updating unit tests and integrity checks, and validating the UI with PySpark, Hive, and Oracle workflows.
Checkpoint on all tickets
Checking point video - all questios and answers explained3:23
Review checkpoints for pip install and virtual environment setup in the Python full stack framework. Identify two workflow types (Python local and Spark large) and timeout and data-related UI issues.
All Slides - Master Deck0:31
All Slides - Master deck
Checkpoint for Full Simulation Full Stack Framework Run
Final Assignment for Ticket and Issue Resolution

Requirements

No programming experience needed

Description

Interview Prep Quant Finance Python Full Stack Computational Framework for Begineers 101

This courses might help you get a job and is very specficly tuned to job requiremnets in Computational Framework.

Solving Tickets for Real life Job Like scenarios - Get ready right now. Very practical course required to get a job in this market. This course help you develop a minset to deliver the good and not to just code.
Learn how to deal with tickets, code changes, python computational framework, get job done.
This course will help you solve tickets and perform in job related to full stack python computational simulation engine. Also will learn how to do testing and software build.
Includes the tests and quiz of real life cases which will help you cater to jobs.
Learn how to use testing and also deal with note makign and reporting to clients in a practical way.
This is not an purely academic course and is very simiular to internal training courses.
Each section comes with a test and helps you gauge and also impress the clients.
Terms and areas touched are Jenkins build, Unit testing, Pytesting, Venv, Spark dataframes, hadoop, schemas, data manipulation, end to end code release framework.
Learn how to change the code from scracth to release in production enviroments.

Who this course is for:

Beginer Python

Python Full Stack Computational Finance Framework Interview

What you'll learn

Explore related topics

Course content

Introduction to Full Stack Computational Framework13 lectures • 10min

Ticket Full Spectrum Testing1 lecture • 4min

Batch runs1 lecture • 4min

Solving Tickets for real job like scenarios21 lectures • 31min

Requirements

Description

Who this course is for: