Python Fundamentals Sprint
Learn Python through guided lessons, hands-on labs, and a mini-project — in just 7 days. No fluff, no 90-minute lecture dumps. Practical skills you can use the next Monday at work.
1-year content access · 7-day refund
What you get
- AI Tutor — concept-aware hints when you're stuck
- 7 days of focused video lessons
- In-browser Python runner — no setup
- Auto-graded exercises with instant feedback
- 1 portfolio mini-project + Jupyter notebooks
- Completion certificate
or $25 outside India
Why this sprint exists
Most beginners fail because they try to learn too much too fast. This sprint covers only what you need to start building — 60–90 focused minutes a day, seven days, one real project at the end.
What you will learn
- Write idiomatic Python using variables, data types, lists, tuples, sets, and dictionaries
- Control program flow with if/else, for/while loops, and comprehensions
- Define reusable functions including lambdas and higher-order patterns
- Apply object-oriented programming — classes, inheritance, encapsulation
- Handle errors safely with try/except and read/write files (text, CSV, JSON)
- Use regular expressions to extract structured data from messy text
- Build and ship an end-to-end email-analyzer mini-project from scratch
Four reasons this sprint beats passive learning
These are what make the Python Fundamentals Sprint different from just watching videos and reading articles. The biggest is the AI Tutor.
+ work for two Python dicts?Dicts don't support + — they're key-value pairs, not sequences.
Use the | operator instead:
merged = store_a | store_b
Want me to show you what happens with overlapping keys?
AI Tutor — concept-aware, code-aware
Stuck on an error or unsure why your code works? Ask the AI Tutor right inside the lesson. It knows which day you're on, what concepts you've been taught, and gives Socratic hints first — not just the answer. Generous turn allowance included; no scheduled TA hours to chase.
Built on Anthropic Claude
In-browser Python — no setup required
Run Python directly in the lesson with a code editor that loads in seconds. No installs, no virtualenv, no Docker. Edit, run, see output. Pair with the AI Tutor and you can iterate without ever leaving the page.
Powered by Pyodide
Auto-graded exercises with instant feedback
Every exercise has a hidden test suite. Click Run, see exactly which tests pass or fail, and the AI Tutor can help you debug the failures. Not just "here's the solution" — interactive, code-level mentorship.
33 exercises across 7 days
$ python email_analyzer.py Wrote report.json with 42 emails
Portfolio-grade capstone, not just slides
Day 7 ships a real project to your GitHub: an Email Analyzer with a clean README. Something you can show in an interview, not just another completion certificate screenshot.
Yours to keep, forever
Day-by-day plan
60–90 minutes a day. Theory, lab, and a small win every single day.
- Free previewDay 1
Variables, Data Types, and Collections
- Python syntax, indentation, and the REPL
- Numbers, strings, booleans, and type conversion
- Lists, tuples, sets, dictionaries — when to use which
Lab: Build a contact-book CLI that stores names and phone numbers in a dictionary.
VideoNotebookLab5 exercisesShow exercise list
- parse_age — defensive integer parsing
- stats — manual min/max/average over a list
- merge_inventory — combine two dict counts
- common_chars — set intersection on lettersstretch
- top_scorers — tuple comprehensionstretch
- Day 2
Flow Control and Looping
- if / elif / else and truthy values
- for and while loops, break and continue
- List, set, and dictionary comprehensions
Lab: Write a FizzBuzz variant + a basic CLI calculator with input validation.
NotebookLab5 exercisesShow exercise list
- grade — score-to-letter bucketing
- fizz_buzz_bang — multi-divisor variants
- char_count — hand-rolled tally
- first_prime_after — break / continuestretch
- pythagorean_complements — pair searchstretch
- Day 3
Functions, Lambdas, and Comprehensions
- Defining functions, default args, *args / **kwargs
- Lambdas, map, filter, reduce
- Scope, closures, and first-class functions
Lab: Refactor day-2 calculator into a function library with a clean public API.
NotebookLab5 exercisesShow exercise list
- discount — default arguments
- flexible_sum — *args / **kwargs
- only_primes — list comprehension
- rank — multi-key sort with lambdastretch
- long_word_lengths — dict comprehensionstretch
- Day 4
Object-Oriented Programming
- Classes, instances, and the self argument
- Inheritance, super(), and method overriding
- Encapsulation and the difference between class and instance attributes
Lab: Model a BankAccount class hierarchy with Savings and Checking subclasses.
NotebookLab5 exercisesShow exercise list
- Rectangle — first real class
- BankAccount — encapsulation rules
- SavingsAccount — inheritance
- Shape hierarchy — polymorphismstretch
- Vehicle ABC — abstract methodsstretch
- Day 5
Exception Handling and File I/O
- try / except / else / finally — when each runs
- Reading and writing text, CSV, and JSON files
- Context managers and the with statement
Lab: Build a CSV log-line analyzer that survives malformed rows gracefully.
NotebookLab5 exercisesShow exercise list
- safe_divide — catch one error class
- withdraw — raise a custom exception
- count_lines — file I/O with fallback
- update_config — JSON round-tripstretch
- parse_grades — CSV with bad rowsstretch
- Day 6
Regular Expressions
- Pattern syntax: character classes, quantifiers, anchors
- Groups, named groups, and substitution
- Common pitfalls — greedy vs lazy matching
Lab: Extract emails, phone numbers, and dates from a noisy text corpus.
NotebookLab5 exercisesShow exercise list
- extract_phones — 10-digit pattern
- is_valid_email — anchored validation
- mask_numbers — re.sub with conditions
- extract_dates — capture groupsstretch
- top_words — word frequency tablestretch
- Day 7
Mini Project — Email Analyzer + Portfolio Cleanup
- Project scaffolding and module structure
- Putting day 1–6 together end-to-end
- Writing a clean README and pushing to GitHub
Lab: Build an Email Analyzer: parses a mailbox file, classifies emails by sender domain, and outputs a JSON report.
VideoNotebookLab3 exercisesShow exercise list
- parse_email_block — parse a single block
- group_by_domain — counting dict
- build_report — JSON-ready summary
What you will build
Concrete artifacts you keep — and can put on your GitHub.
- Contact-book CLI (Day 1)
- FizzBuzz + CLI calculator (Day 2)
- Function library refactor (Day 3)
- Bank-account class hierarchy (Day 4)
- CSV log-line analyzer (Day 5)
- Regex-powered data extractor (Day 6)
- Email Analyzer end-to-end portfolio project (Day 7)
What's included in the download bundle
Every notebook, video, lab PDF, and reference solution you'll need. Unlocked in your learner dashboard the moment payment confirms.
- Day 1 — Variables, Data Types, and Collections
Jupyter notebook · Day 1 ·
Day1-Variables-Data-Types-and-Collections.ipynb - Day 2 — Flow Control and Looping
Jupyter notebook · Day 2 ·
Day2-Flow-Control-and-Looping.ipynb - Day 3 — Functions, Lambdas, and Comprehensions
Jupyter notebook · Day 3 ·
Day3-Functions-Lambdas-and-Comprehensions.ipynb - Day 4 — Object-Oriented Programming
Jupyter notebook · Day 4 ·
Day4-Object-Oriented-Programming.ipynb - Day 5 — Exception Handling and File I/O
Jupyter notebook · Day 5 ·
Day5-Exception-Handling-and-File-IO.ipynb - Day 6 — Regular Expressions
Jupyter notebook · Day 6 ·
Day6-Regular-Expressions.ipynb - Day 7 — Mini Project Walkthrough
Jupyter notebook · Day 7 ·
Day7-Mini-Project-Email-Analyzer.ipynb - Daily exercises (Day1–Day7)
Source file ·
Day1-Exercises.py through Day7-Exercises.py - Day 1 · Part 1 — Variables and Operators
Video lesson · Day 1 ·
Day1-01-Variables-and-Operators.mp4 - Day 1 · Part 2 — Data Types and Type Conversion
Video lesson · Day 1 ·
Day1-02-Data-Types-and-Conversion.mp4 - Day 1 · Part 3 — Lists and Tuples
Video lesson · Day 1 ·
Day1-03-Lists-and-Tuples.mp4 - Day 1 · Part 4 — Sets and Dictionaries
Video lesson · Day 1 ·
Day1-04-Sets-and-Dictionaries.mp4 - Day 1 · Part 5 — Practice and Lab Brief
Video lesson · Day 1 ·
Day1-05-Practice-and-Lab-Brief.mp4 - Mini-Project Assignment Brief
PDF · Day 7 ·
Mini-Project-Assignment.pdf - Mini-Project starter — Email Analyzer
Source file · Day 7 ·
EmailAnalyzer.py - Reference solution — Email AnalyzerOptional
Source file · Day 7 ·
EmailAnalyzer-Solution.py - Reference solution — Email ValidationOptional
Source file · Day 7 ·
EmailValidator-Solution.py
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How access works
- 1
Enroll
Pay securely via Cashfree. Indian and international cards, UPI, and net-banking supported.
- 2
Get your login by email
A welcome email from info@skildock.com lands in your inbox immediately, with your account credentials and a one-click login link.
- 3
Start Day 1
Log in at learn.skildock.com, set your own password, and start streaming Day 1 right away. Progress is auto-saved.
Forgot your password? Reset from the login screen at any time — a code is emailed by info@skildock.com.
Get notified when the Python Fundamentals Sprint opens
Self-paced, 7 days of lessons, 1-year content access. Waitlist members get a launch-day discount — typically 30–40% off the regular ₹999.
Frequently asked questions
What is the AI Tutor and is it really useful?
A built-in AI helper, available on every lesson page. It knows which day you're on, which concepts you've been taught so far, and gives Socratic hints first — not the full answer — so you actually learn. Powered by Anthropic Claude. The Standard sprint includes a generous turn allowance over a 21-day active window, plenty for honest learners. Heavier-use packages will be available later for power users.
Do I need any programming experience before starting?
No. The sprint assumes zero prior programming experience. We start with the absolute basics on Day 1 and build up to a real project by Day 7.
How much time per day do I need?
Plan for 60–90 minutes per day — about 30 minutes of theory video plus 30–60 minutes of hands-on lab work. Easy to fit around a full-time job.
What do I get after I pay?
An account on learn.skildock.com with 1-year access to all 7 days of video lessons, Jupyter notebooks, lab solutions, and the mini-project. You'll receive your login credentials by email immediately after payment.
Can I get a refund if it's not for me?
Yes — we offer a 7-day no-questions refund if you've consumed less than 30% of the content. Just write to info@skildock.com.
Is there live support if I get stuck?
You can email info@skildock.com any time and our team responds within one business day. Live cohort support is part of our longer Career Programs.
Do I get a certificate?
Yes, you receive a downloadable completion certificate once you've finished all 7 days and submitted the mini-project.
What's the difference between this and the full Python Backend Engineering course?
The sprint gets you confident with Python fundamentals in a week. The 14-week Python Backend Engineering program goes deep into FastAPI, databases, async, Docker, and shipping production APIs — it's a career-transition program, not a fundamentals primer.