Data cleaning and reporting script
Deliverable: A script that ingests a messy real-world CSV, validates and cleans it, and writes a summary report, with logging and a test suite covering the edge cases you found.
Course
Python Programming
Python taught as a working tool rather than a syntax tour — you finish able to read unfamiliar code, automate real tasks, call APIs and write tests that catch your own mistakes.
- Duration: 4 months
- Classroom · Online live
- Level: beginner to advanced
What you will be able to do
- Write, structure and debug Python programs of several hundred lines without getting lost
- Read unfamiliar Python code and work out what it does before changing it
- Handle files, CSVs, JSON and APIs, and turn messy input into structured data
- Automate a repetitive task end to end so it runs without manual steps
- Write tests that fail when the code is wrong, and use them while refactoring
- Use virtual environments, packages and Git the way a working team does
Who this course is for
- Graduates and final-year students from any stream
- Working professionals automating repetitive tasks in their current role
- Anyone planning to move into data, testing, backend or AI work later
- No prior programming experience required
Syllabus
7 modules · 4 months
Module 1. Core language
- Values, types, variables and the mental model behind them
- Conditionals, loops and how to avoid nesting yourself into a corner
- Lists, tuples, dictionaries and sets, and choosing between them
- Functions, arguments, return values and scope
- Reading a traceback and debugging deliberately rather than by guessing
Module 2. Structuring real programs
- Modules, packages and imports
- Comprehensions and generator expressions
- Errors and exceptions as control flow
- Classes and objects, and when a class is the wrong tool
- Virtual environments and dependency management
Module 3. Working with data
- Reading and writing files safely
- CSV and JSON parsing
- Dates, times and the mistakes everyone makes with them
- pandas basics for tabular work
- SQLite from Python
Module 4. The outside world
- HTTP and REST in plain terms
- Calling APIs with requests, and handling failure
- Rate limits, retries and timeouts
- Web scraping, and the legal and ethical limits on it
Module 5. Automation
- Command-line scripts with arguments
- Scheduling a script to run unattended
- Logging so you can diagnose a failure after the fact
- Working with spreadsheets and PDFs programmatically
Module 6. Testing and quality
- Why tests are faster than manual checking
- pytest, assertions and fixtures
- Refactoring behind a test suite
- Type hints and what they catch
Module 7. Portfolio and interviews
- Turning coursework into a readable repository
- Python interview question practice
- Live coding practice under time pressure
Tools and technologies you will use
- Python 3
- pip and virtual environments
- requests
- pandas
- pytest
- Git and GitHub
- VS Code
- SQLite
Projects you will build
API-backed command-line tool
Deliverable: A command-line tool that calls a public API, handles rate limits and network failures gracefully, caches responses, and is documented well enough for someone else to run.
Automation of a repetitive task
Deliverable: A scheduled script that automates a genuinely repetitive task, with a written before-and-after note on the time it saves and what it does when it fails.
Small database-backed application
Deliverable: A Python application with SQLite persistence, a clear module structure and a test suite that runs from a clean checkout.
Where this course can take you
- Python Developer
- Automation Engineer
- Backend Developer
- Data Analyst
- QA Automation Engineer
Duration, modes and fees
- Duration
- 4 months
- Delivery modes
- Classroom · Online live
- Fees
- Share your details for the current fee
- Fees vary by batch and delivery mode. Share your details and an advisor will confirm the current fee.
Placement assistance
Every student gets placement assistance — that is what 100% placement assistance means. It is support for all, not a job for all. We do not promise a specific salary, a specific number of interviews, or placement at any named company, and you should be wary of anyone who does.
What is included
- A place in the monthly placement drive, held every third Saturday
- The readiness programme every second Saturday — mock interviews and preparation
- CV review against the specific roles you are targeting
- Portfolio review, so your project work is presented the way a reviewer will read it
- Access to the vacancy pool employers send directly to the Samyak network
- Guidance on which roles realistically fit your background and which do not
- A place in the next drive, with coaching, if you are not selected in this one
What is not included
- Any guarantee of a job, an interview, or a particular salary
- Placement at a named or partner company
- Applying to jobs on your behalf
- Support before you have completed the course and its project work
- Visa, relocation or overseas placement assistance
Why this course is longer than it looks like it should be
You can learn Python syntax in a fortnight. Plenty of courses stop there, and their graduates can follow a tutorial but freeze when handed a real problem.
The gap is not knowledge, it is fluency — the ability to sit with an unfamiliar error, form a hypothesis, and test it. That only comes from writing a lot of code that does not work at first. So this course front-loads the language in the first six weeks and then spends the remaining time on progressively less guided work, ending with projects where you choose the approach.
Debugging is taught, not assumed
Most courses never teach debugging. They demonstrate working code, and when yours breaks you are on your own. We treat reading a traceback as a skill with a method: read it bottom-up, find the line, check your assumptions about the data before your assumptions about the logic.
Learners consistently say this is the part that changed how the rest of the course felt.
What we do not cover, and why
No Django, no Flask, no machine learning. Each is a serious subject and bolting a two-week version onto a language course produces the illusion of coverage without the substance. When you finish this course you will be equipped to take any of them on properly — and our full stack and AI courses do exactly that.
Questions
Python Programming — frequently asked questions
Is Python enough on its own to get a job?
Rarely, and it is worth being honest about that. Python is the language; employers hire for what you do with it. Pair it with SQL and data work for analyst roles, or with a web framework and databases for backend roles. This course teaches the language properly so that the next step, whichever it is, is straightforward.
How long does it take to learn Python properly?
Four months of consistent practice gets you to genuine working competence — able to build things and read other people's code. You can learn the syntax in two weeks; the gap between knowing the syntax and being able to build something is where the remaining time goes, and it is entirely practice.
Should I learn Python or Java first?
For most people starting out, Python. Its syntax gets out of the way while you are learning to think about programming, and it opens directly into data, automation and AI work. Java remains strong in large enterprise environments, and if you have a specific employer in mind who uses it, learn that instead.
Do I need a maths background for Python?
No. General programming, automation and web work need almost no mathematics beyond school arithmetic. If you later move into data science or machine learning you will need statistics, but that is a separate course and a separate decision.
Will this course cover Django or Flask?
No, deliberately. Web frameworks are a large subject and covering one shallowly at the end of a language course helps nobody. This course makes you genuinely competent in the language and its ecosystem; our full stack course covers web application development properly.
Enquire about Python Programming
Three details is all we need. A course advisor will call you back.
Related courses
- Data Analytics
A structured path from spreadsheets to SQL, Power BI and Python, built around the four things a data analyst is actually paid to do — pull the data, clean it, analyse it and explain it.
- Artificial Intelligence
Python, machine learning foundations and applied generative AI in one track — ending with a retrieval-augmented application you have built, evaluated and can explain end to end.
- Full Stack Development
Front end, back end, databases and deployment taught as one connected system, ending with applications you have shipped to a public URL and can walk an interviewer through.
Next step
Talk to a course advisor
Tell us what you want to learn and we will help you pick the right course, batch and mode.