Complete Python And Projects — Mega Compilation
Everything that you need to know in Python with Projects…
Welcome back peeps. This post covers everything you need to know in Python right from basics to advanced level and some python projects that you can implement.
Advanced SQL Series
Day 2 : SQL Basics, Query Structure, Built In functions Conditions
Day 4 : Set Theory Operations, Stored Procedures and CASE statements in SQL
Day 6 : Subqueries, Group by, order by and Having clauses in SQL and Analytical Functions
Day 7 : Window Functions, Grouping Sets and Constraints in SQL
Day 8 : BigQuery Basics, SELECT, FROM, WHERE and Date and Extract in BigQuery
Day 9 : Common Expression Table, UNNEST Clause, SQL vs NoSQL Databases
Day 10 : Triggers, Pivot and Cursors in SQL
Day 14 : MySQL in Depth
Day 15 : PostgreSQL inDepth
Projects Videos —
All the projects, data structures, SQL, algorithms, system design, Data Science and ML , Data Analytics, Data Engineering, , Implemented Data Science and ML projects, Implemented Data Engineering Projects, Implemented Deep Learning Projects, Implemented Machine Learning Ops Projects, Implemented Time Series Analysis and Forecasting Projects, Implemented Applied Machine Learning Projects, Implemented Tensorflow and Keras Projects, Implemented PyTorch Projects, Implemented Scikit Learn Projects, Implemented Big Data Projects, Implemented Cloud Machine Learning Projects, Implemented Neural Networks Projects, Implemented OpenCV Projects,Complete ML Research Papers Summarized, Implemented Data Analytics projects, Implemented Data Visualization Projects, Implemented Data Mining Projects, Implemented Natural Leaning Processing Projects, MLOps and Deep Learning, Applied Machine Learning with Projects Series, PyTorch with Projects Series, Tensorflow and Keras with Projects Series, Scikit Learn Series with Projects, Time Series Analysis and Forecasting with Projects Series, ML System Design Case Studies Series videos will be published on our youtube channel ( just launched).
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All the Complete System Design Series Parts —
6. Networking, How Browsers work, Content Network Delivery ( CDN)
System Design Case Studies — In Depth
Design Instagram
Design Netflix
Design Reddit
Design Amazon
Design Messenger App
Design Twitter
Design URL Shortener
Design Dropbox
Design Youtube
Design API Rate Limiter
Design Web Crawler
Design Amazon Prime Video
Design Facebook’s Newsfeed
Design Yelp
Design Uber
Design Tinder
Design Tiktok
Design Whatsapp
Most Popular System Design Questions
Mega Compilation : Solved System Design Case studies
Complete Data Structures and Algorithm Series
Github —
Github —
Complete Advanced Python with Projects — Mega Compilation Part 6
Python is a high-level, most widely used multi-purpose, easy to read programming language.
It is —
- Interpreted − Python is processed at runtime by the interpreter. i.e you do not need to compile your program before executing it
- Interactive − You can interact with the interpreter directly to write your programs
- Portable — It can run on wide range of hardware Platforms
- Object-Oriented − Python supports Object-Oriented style and Procedural Paradigms
- Used as a scripting language or can be compiled to byte-code for building large applications
- It has simple structure, and a clearly defined syntax
- Known as Beginner’s Language − It’s a great language for the beginner-level programmers
- Source code is comparatively easy-to-maintain
- Provides very high-level dynamic data types and supports dynamic type checking.
- Has a huge collection of standard library
So start your journey from here —
Day 1 : Python Basics with Code Implementation — Part 1
In this post we covered end to end Python Basics ( Part 1) that you should know. Topics like data types, strings, operators, and Chaining Comparison Operators with Logical Operators are covered.
Where to find Day 1 post :
Highly Recommended Data Science and Machine Learning Courses that you MUST take ( with certificate) —
Find best data science and data engineering courses here
Find best Machine Learning and Deep Learning courses here
Day 2: Python Basics with Code Implementation — Part 2
In this post we covered end to end Python Basics ( Part 2) that you should know. Topics like Python Lists and Dictionaries, Sets, Tuples etc are covered in detail.
Where to find Day 2 post :
Day 3: Python Basics with Code Implementation — Part 3
In this post we covered end to end Python Basics ( Part 3) that you should know. Topics like Tuples, Sets, Loops, Break and Continue Statements, Object-Oriented Programming and Class and attributes in Python are covered in detail.
Where to find Day 3 post :
Day 4: Complete Python Strings
In this post we covered Python strings in detail. Python strings are arrays of bytes representing unicode characters. Strings in python are surrounded by either single quotation marks, or double quotation marks.
Where to find Day 4 post :
Day 5 : Underscores(_) in Python
Underscores are unique characters in Python and helps users write code productively. In this post we explored how you can use single and double underscore in your code.
Where to find Day 5 post :
Day 6: Python’s F-Strings
In this post we covered Python’s F-string. Python F-String are used to embed python expressions inside string literals for formatting, using a minimal syntax. It’s an expression that’s evaluated at the run time. They have the f prefix and use {} brackets to evaluate values. f-strings are faster than %-formatting and str.format().
Where to find Day 6 post :
Day 7: Python — Map, Classes, Functions and Arguments with Implementation
Where to find Day 7 post :
Day 8: Intermediate Python with Code Implementation — Part 1
In this post we covered end to end Intermediate Python ( Part 1) that you should know. Topics like First Class functions, Private Variables, Global and Non Local Variables, __import__ function, Magic Functions, Tuple Unpacking, Static Variables and Methods in Python are covered in detail.
Where to find Day 8 post :
Day 9: Intermediate Python with Code Implementation — Part 2
In this post we covered end to end Intermediate Python( Part 2) that you should know. Topics like Lambda Functions, Magic methods, Inheritance and Polymorphism, Errors and Exception Handling, User-defined functions, Python garbage collection, and debugger are covered in detail.
Where to find Day 9 post :
Day 10 : Python Iterators, Generators And Decorators Made Easy
In this post we covered basics, implementation, and how to Iterators, Generators, and Decorators in your code.
Where to find Day 10 post :
Day 11: Advanced Python with Code Implementation
In this post we covered end to end Advanced Python that you should know. Topics like Decorators, Memoization using Decorators, Generators, Ordered and Defaultdict, Coroutine with Code implementation are covered in detail.
Where to find Day 11 post :
Day 12: Advanced Python with Code Implementation
In this post we covered Regular expression, Magic methods, Closures in detail.
Where to find Day 12 post :
Day 13: Advanced Python with Code Implementation
In this post we covered DefaultDict, decorator , Memoization using Decorators, Lambda Functions in detail.
Where to find Day 13 post :
Day 14: Advanced Python with Code Implementation
In this post we covered DefaultDict, decorator , Memoization using Decorators, Lambda Functions in detail.
Where to find Day 14 post :
Day 15: Advanced Python with Code Implementation
In this post we took a deep dive in Python’s Itertools. Python Itertools are fast, memory efficient functions — a collection of constructs for handling iterators. Iterators are nothing but an object that contains a countable number of value i.e values you can traverse through and can be Infinite iterators, Combinatoric iterators, Terminating iterators. List, tuples, dictionaries, and sets are all iterable objects.
Where to find Day 15 post :
Day 16: Advanced Python with Code Implementation
In this post we covered some advanced python constructs that will help you write efficient code, improve code readability and performance.
Where to find Day 16 post :
Day 17: Advanced Python with Code Implementation
In this post we covered ChainMap in Python in detail.
Where to find Day 17 post :
Day 18: Advanced Python with Code Implementation
In this post we covered Comprehensions, Named Tuple, Type hinting in Python in detail.
Where to find Day 18 post :
Day 19 : Write Efficient Code
Learn how to write efficient Code in Python
Where to find Day 19 post :
Writing Efficient Python Code — Part 2
Use these hacks and techniques…
medium.datadriveninvestor.com
Day 20 : Efficient Code and Optimization techniques for Python
Where to find Day 20 post :
Python One liners
Efficient Code and Optimization techniques for Python
Day 21–25 : Projects —
Analyzing Video using Python, OpenCV and NumPy
Cluster Analysis using Python — Part 1
Clustering Geolocation Data in Python using DBSCAN and K-Means
Must Learn Python Libraries
Four “Lesser Known” Python Libraries for Data Science
Follow for more updates. Stay tuned and keep coding! Some of the links are affiliates.
Last Day — Summarize
Python Crash Course — Part 1 ( Covers all the Basics)
Python Crash Course — Part 2 ( Covers Advanced Python)
For Complete Data Science and Machine Learning with projects series —
Some of the other best Series —
How to solve any System Design Question ( approach that you can take)?
100 days : Your Data Science and Machine Learning Degree Series with projects
Complete Data Visualization and Pre-processing Series with projects
Tech Newsletter —
If you are interested, you can join my newsletter through which I send tech interview tips, techniques, patterns, hacks — Software Development, ML, Data Science, Startups and Technology projects to more than 30K readers. You can subscribe to Tech Brew :
30 days of Data Analytics Series —
Day 1 : Data Analytics basics and kickstart of Data analytics with projects series
Day 3 : Data Analytics Ecosystem — Data Life Cycle, Data Analysis complete process ( most important things)
Day 5 : Statistics
Day 6 : Basic and Advanced SQL
Day 8 : Pandas and Numpy
Day 9 : Data Manipulation
Day 10 : Data Visualization — Part 1
Day 11 : Project 1 : Data Visualization — Part 2
Day 12 : Data Visualization — Part 3
Day 13: Tableau — Part 1
Day 14: Tableau — Part 2
Day 15: Tableau — Part 3
Day 16 : Data Analysis Project 2
Day 17 : Data Analysis Project 3
Day 18: Data Analysis Project 4
Day 20 : Data Analysis Project 6
Day 21 : Data Analysis Project 7
Take Complete Hands On Tableau Course : Link
Advanced SQL Series
Day 2 : SQL Basics, Query Structure, Built In functions Conditions
Day 4 : Set Theory Operations, Stored Procedures and CASE statements in SQL
Day 6 : Subqueries, Group by, order by and Having clauses in SQL and Analytical Functions
Day 7 : Window Functions, Grouping Sets and Constraints in SQL
Day 8 : BigQuery Basics, SELECT, FROM, WHERE and Date and Extract in BigQuery
Day 9 : Common Expression Table, UNNEST Clause, SQL vs NoSQL Databases
Day 10 : Triggers, Pivot and Cursors in SQL
Day 14 : MySQL in Depth
Day 15 : PostgreSQL inDepth
Anyways, For Day 15 of 15 days of Advanced SQL, we will cover —
PostgreSQL inDepth
Github for Advanced SQL that you can follow —
All the projects, data structures, algorithms, system design, Data Science and ML, Data Engineering, MLOps and Deep Learning videos will be published on our youtube channel ( just launched).
Subscribe today!
System Design Case Studies — In Depth
Complete Data Structures and Algorithm Series
Github —
For other projects, tune to —
Build Machine Learning Pipelines( With Code)
Recurrent Neural Network with Keras
Clustering Geolocation Data in Python using DBSCAN and K-Means
Facial Expression Recognition using Keras
Hyperparameter Tuning with Keras Tuner
Custom Layers in Keras
