BookTown | Python Coding Batch

📚 Choose Your Learning Path

✨ Batch Highlights

Learn Python from Scratch

No experience needed – progressive learning

Build Real Projects

Calculator, quiz system, student database

Git + Linux + SQL

Industry tools integrated naturally

1‑Hour Daily Sessions

Focused, effective, no burnout

Your Learning Journey

Python FundamentalsMonth 1

Intermediate Python + LinuxMonth 2

Databases + Advanced PythonMonth 3

📅 3‑Month Learning Path

Month 1

Python basics + Git

Conditionals, loops, lists, version control

Month 2

Intermediate Python + Linux

Functions, OOP, file ops, terminal commands

Month 3

Databases + Final Project

SQLite, APIs, library management system

🛠️ Technologies You'll Master

🐍

Python

Fundamentals, OOP, modules, file I/O, APIs

Variables Loops OOP

🔀

Git & GitHub

Version control, branching, collaboration

commit push merge

🐧

Linux

Terminal commands, file system, permissions

bash grep ls

🗄️

SQL (SQLite)

CRUD, JOIN, aggregate functions, data import/export

SELECT JOIN CREATE

📖 Detailed Curriculum

Schedule: 5 days/week (Mon–Fri) | 1 hour/day | In‑person only

Month	Focus	Weekly Structure
Month 1	Python Basics + Git	4 days Python + 1 day Git
Month 2	Python Intermediate + Linux	4 days Python + 1 day Linux
Month 3	Python + Database (SQLite)	2 days Python + 2 days DBMS + 1 day Project

Month 1 – Python Fundamentals & Git

Week	Python (4 days)	Git (1 day)
1	Print, variables, input, conditionals	Install, init, add, commit
2	Loops (for/while), nested loops	Branching, merging
3	Lists, tuples, list comprehension	GitHub: push, pull, clone
4	Dictionaries, sets, file I/O	Remote repo & collaboration

Month 2 – Python Intermediate & Linux

Week	Python (4 days)	Linux (1 day)
5	Functions, parameters, recursion	Navigation: ls, cd, mkdir, rm
6	Error handling, modules (random, math)	File ops: cp, mv, grep, wc
7	OOP basics: classes, objects, inheritance	Permissions (chmod), processes (ps, kill)
8	List comprehensions, lambda, map/filter	Networking: ping, curl, ssh basics

Month 3 – Python Advanced + Database

Week	Python (2 days)	Database (2 days)	Project/Revision (1 day)
9	Iterators, generators, decorators	SQLite: CREATE, INSERT, SELECT, UPDATE	Project planning
10	JSON, APIs (fetch weather/jokes)	JOIN, GROUP BY, aggregate functions	API + DB integration
11	Python + SQLite integration	CRUD, CSV import/export	Build core features
12	Final Project (Library Management System)	DB design & optimization	Testing & presentation

✅ By course end: Build a complete database-driven application and present your portfolio.

📅 Batch Schedules

🔵 Batch 1

⏰ Schedule: Wednesday to Sunday (1 hour daily)

💰 Fee: ₹2,500/month or ₹7,000 for full course

🟢 Batch 2

⏰ Schedule: Friday (1h) + Saturday (2h) + Sunday (2h)

💰 Fee: ₹2,500/month or ₹7,000 for full course

💡 Both batches cover the same curriculum at the same pace – choose the timing that fits you.

6-Month Professional Roadmap

Months 1–2: Python mastery + 100+ DSA problems (sorting, hashing, recursion)

Month 3: FastAPI fundamentals + REST API design

Month 4: Advanced API + PostgreSQL + async/await + production patterns

Months 5–6: AI/ML integration + RAG systems + capstone project

🎯 Final Outcome: Portfolio-ready projects + interview-ready competency

Months 1 & 2 – Python + Sorting Algorithms + DSA

Month	Week	Core Topics	LeetCode/HackerRank	Key Skills
Month 1	Week 1	Python refresher: data types, I/O, loops, functions, lists, dicts, sets	Easy: Two Sum, Contains Duplicate, Valid Anagram	map, filter, zip, enumerate, comprehensions
	Week 2	Iterative Sorting: Bubble, Selection, Insertion Sort	Easy: Merge Sorted Array, Sort By Parity	Complexity analysis, timeit, sorted() with key
	Week 3	Strings, arrays, hashing \| Two-pointer, sliding window	Medium: Longest Substring, Group Anagrams, Top K	Counter, defaultdict, lambda sorting
	Week 4	Recursion basics & backtracking introduction	Factorial, Fibonacci, Generate Parentheses, Subsets	lru_cache, recursion depth, yield
Month 2	Week 5	Divide & Conquer: Merge Sort (recursive)	Medium: Sort an Array, Count Smaller Numbers	List slicing, index manipulation, itertools
	Week 6	Quick Sort – pivoting, partitioning	Quick Select, Kth Largest, Sort Colors	random.choice, in-place swaps, cmp_to_key
	Week 7	Heap & Heap Sort – heapq module, priority queues	Medium: Kth Largest in Stream, Top K Words	heapq methods, __lt__ for custom objects
	Week 8	DSA review sprint – mixed problems, timed contests	30+ selected LeetCode Medium/Hard problems	All above + decorators, profiling, optimization

✅ Month 2 Deliverable: Polished Python package with all sorting algorithms + 50+ DSA solutions

Month 3 – API Development Fundamentals

Week	Core Topics	Hands-On Project	Skills
9	HTTP, REST, FastAPI setup, path/query params, Pydantic validation	CRUD API for Books collection	Type hints, Pydantic models, uvicorn
10	Request body, error handling, status codes, file uploads	Books API with image upload	shutil, aiofiles, HTTPException
11	Dependency injection, middleware, CORS, background tasks	Weather API proxy with caching	BackgroundTasks, lru_cache, httpx async
12	Testing (pytest, TestClient), OpenAPI docs, Docker	Containerise, write unit & integration tests	pytest, Dockerfile, docker-compose, Swagger

✅ Month 3 Deliverable: Fully tested, containerised REST API + portfolio project

Month 4 – Advanced API + PostgreSQL

Week	Core Topics	DBMS & Async	Milestone
13	SQLAlchemy ORM, Alembic migrations, PostgreSQL, CRUD	Define tables, relationships, seed data	Task Manager API start
14	Advanced Pydantic, nested models, response separation	One-to-many, many-to-many relationships	User registration, JWT login
15	Async endpoints, asyncio, Celery/Redis, notifications	Async DB queries, aiosmtplib background jobs	Email notifications on task assignment
16	Exception handlers, logging (loguru), rate limiting	Custom exceptions, logging middleware, slowapi	Docker stack (API + DB + Redis), finalize

✅ Month 4 Deliverable: Production Task Manager API with auth, async, logging, Docker

Months 5 & 6 – Applied AI/ML (Capstone)

Month	Week	AI/ML Topics	API Integration	Capstone
Month 5	17	CNN optimization, ONNX, quantization	Serve CNN from API, Redis caching	Agri-Tech AI Platform Start
	18	NLP, Transformers (Hugging Face), embeddings	FAQ chatbot endpoint, log conversations	FAQ module: semantic search
	19	RAG: Vector stores (FAISS), chunking, retrieval	PDF upload, extract, embeddings, Q&A endpoint	Document indexing + retrieval
	20	Advanced RAG: LLM (Gemini/Ollama), streaming	Async streaming, Server-Sent Events, caching	Natural language Q&A + citation
Month 6	21	MLOps: Prometheus, CI/CD (GitHub Actions), deployment	Health checks, dashboards, auto-redeploy	Deploy publicly (Render/AWS)
	22	Testing AI, graceful fallbacks, retries	Pytest AI components, mock external calls	Harden API, error recovery
	23	User management, tiered access, priority queues	Rate limiting, async image classification	Feature polish, optimization
	24	Portfolio polish, GitHub docs, final demo	Code walkthrough, detailed README, diagrams	Complete: Disease Detection + PDF Q&A

✅ Final Capstone: Agri-Tech AI Platform API

🔍 Plant Disease Detection – upload image → CNN prediction (optimized & cached)

📚 Document Q&A – upload PDFs, ask questions, RAG + streaming responses

👤 User Dashboard – JWT auth, request history, tiered access

⚡ Production Ready – async processing, monitoring, auto-scaling

Program Outcomes

100+ DSA

Optimised solutions across all patterns

Two APIs

Books + Task Manager (production-ready)

AI/ML System

Deployed, containerised capstone

Interview Ready

Deep skills + portfolio projects

💰 6-Month Program Investment

₹3,000/month

or ₹15,000 for full 6-month (save ₹3,000)

✅ Live sessions + 1-on-1 mentorship | ✅ Project code reviews | ✅ Career guidance

Enroll 6-Month Program

💻 Easy DSA Questions – Build Your Foundation

Practice essential data structure problems to strengthen your problem-solving skills before advanced DSA.

1. Two Sum

Difficulty: Easy

Given an array of integers and a target, find two numbers that add up to the target.

            Input: [2,7,11,15], target = 9

            Output: [0,1]

➡️ See Solution

def twoSum(arr, target):\n    seen = {}\n    for i, num in enumerate(arr):\n        complement = target - num\n        if complement in seen:\n            return [seen[complement], i]\n        seen[num] = i\n    return []

2. Contains Duplicate

Difficulty: Easy

Check if an array contains any duplicate elements.

            Input: [1,2,3,1]

            Output: True

➡️ See Solution

def containsDuplicate(arr):\n    return len(arr) != len(set(arr))

3. Valid Anagram

Difficulty: Easy

Check if two strings are anagrams of each other.

            Input: "listen", "silent"

            Output: True

➡️ See Solution

def isAnagram(s, t):\n    return sorted(s) == sorted(t)

4. Majority Element

Difficulty: Medium

Find the element that appears more than n/2 times.

            Input: [3,2,3]

            Output: 3

➡️ See Solution

def majorityElement(arr):\n    count = {}\n    for num in arr:\n        count[num] = count.get(num, 0) + 1\n    return max(count, key=count.get)

5. Merge Sorted Arrays

Difficulty: Medium

Merge two sorted arrays into a single sorted array.

            Input: [1,3,5], [2,4,6]

            Output: [1,2,3,4,5,6]

➡️ See Solution

def mergeSorted(arr1, arr2):\n    return sorted(arr1 + arr2)

6. Reverse String

Difficulty: Medium

Reverse a string in place (modify the list).

            Input: "hello"

            Output: "olleh"

➡️ See Solution

def reverseString(s):\n    return s[::-1]

💡 Practice Tips

Start Simple: Begin with Easy questions to build confidence
Solve Without Looking: Try to solve before checking the solution
Understand Complexity: Analyze time & space complexity of your solutions
Use Multiple Approaches: Find both brute force and optimized solutions
Practice Regularly: Solve at least 2-3 questions daily for consistency

👨‍🏫 Your Instructor

Industry expert with deep expertise in Python, APIs, AI/ML, and full-stack development

Mohd Tayyab

Full-Stack Developer & AI/ML Expert

10+ years software development | AI/ML specialist | Passionate about building intelligent systems with Python. Industry mentor and course architect.

Python APIs AI/ML Backend Data Science

💬 1-on-1 doubt clearance & mentorship available — Get personalized guidance and doubt resolution from the course instructor.

🤔 Why Choose This Course?

Beginner → Intermediate

Structured path from zero to confident coder.

Industry Skills

Python, Git, Linux, SQL – daily developer toolkit.

Peer Learning

Collaborative environment, mentorship included.

Project Portfolio

6+ real projects to showcase.

Focused Sessions

1 hour daily – consistent progress without overload.

In-Person Mentorship

Direct support, instant doubt resolution.

🚀 Ready to become a coding pro?

Limited seats per batch. Enroll now for a free demo class.