15 Days roadmap to master #Python basics for #DataScience & #MachineLearning without having any Prior Experience.

[ Join the #100DaysOfCode & #66daysofdata challenge to keep yourself motivated ]

Thread 🧵👇
Few things to keep in mind before starting
- Learn By Doing, Practicing & Not Just Reading
- Code By Hand [very effective]
- Share, Teach, Discuss and Ask For Help
- Use Online Resources
- Be consistent
- Learn to Use Debugger
I have done all the below-mentioned concepts as part of the #100DaysOfCode challenge and the code can be found in my @github profile.

[Projects & exercise not done. let me know if you want the solutions]

github.com/Piyal-Banik/10…
Day 1

Python Introduction
- Overview
- Python interpreter
- Setup machine (Jupyter Notebook / @Replit )
- Input & Output
- Write your first Python program which can ask a user for input and then display it.
Day 2

- Get familiar with built-in data types [Bool, Int, Float, List, Tuple, String, Set, Dict], no need to go in-depth yet.
- Learn about various operators [Logical, Equality, Comparison, Arithmetic]

Exercise
- Try writing expressions to check all the operators.
Day 3

- Conditional execution (if-else statements)
- Iterations (for & while loops)

Exercise (using both loops)
- Accept number from user and calculate the sum of all numbers from 1 to the given number
- Write a program to display all prime numbers within a range
Day 4

- Functions
- Python's built-in functions
- Exception handling

Exercise
- Write a short Python function, isMultiple(n, m), that takes two integer values and returns True if n is a multiple of m and False otherwise.
Day 5: Mini Projects

- Write a Python function that takes a sequence of int values & determines if there is a distinct pair of numbers in the sequence whose product is odd.
-Write a Python function that takes a sequence of numbers and determines if all the numbers are different.
Day 6

Spend the entire day on Strings
- Slicing
- Modify
- Concatenate
- Format
- String methods

Exercise
- Write a short Python function that counts the number of vowels in a given character string.
- Python program to check whether a string is Symmetrical or Palindrome
Day 7

Work on Lists & Tuples
- Access list items
- Change list item
- Add list item
- Remove list item
- Loop lists
- Comprehension
- Sort
- Copy list
- Join list

Exercise
- Write a program that outputs all possible strings formed by using: c, a, t, d, o, g exactly once.
Day 8

Tuples, Sets, Dictionaries
- Access items
- Add items
- Remove items
- Loop items
- Built-in methods

Exercise
- Find the sum of all items in a dictionary
- Join 2 Tuples if they have similar initial element
- Maximum and Minimum in a Set
Day 9

File Handling
- Read files
- Write files
- Search a file
- Delete files

Exercise
- Write a program to read through a file and print the contents of the file (line by line) all in upper case.
Day 10

Regular expressions
- Match Function
- Search Function
- Replace Function
- Patterns
- Option Flags
Day 11

Object-Oriented Programming
- Class definitions
- Using Objects
- Inheritance
- Abstraction
- Magic Methods

Exercise
- Try to implement Gaussian & Binomial Distributions using OOP
Day 12 - Project 1

Rock 🪨, Paper 🗞️, Scissors ✂️ Game

One of the most beloved games of all time and a simple Python project to test your skills. Start by making it player vs computer.

Skills used: Gain a better understanding of while loops and if statements.
Day 13 - Project 2

Guess🤔The Number

A fun Python project for groups or events where a random generator is needed. It’s useful for conducting lotteries, board games.

Skills used: Getting familiar with the random function, variables, integers, print, if/else, and while loops.
Day 14 - Project 3

Hangman 🕺

This Python game substitutes a word where the user guesses the letters. You will also need to create a counter to count the number of guesses of the wrong letters.

Skills used: Random library, boolean, input/output, char, string, and length.
Day 15

Review Everything that you have learned so far
- Python Introduction
- Built-in Data Types
- Operators
- Conditionals
- Iterations
- Functions
- Exceptions
- Strings
- Lists
- Tuples
- Sets
- Dictionaries
- Files
- Regular Expression
- Object-Oriented Programming
I would highly recommend getting a free copy of the book "Python for Everybody" - by Dr. Charles & R. Severance
py4e.com/book.php

In case you want to join a course then I would recommend - "Python for Everybody" offered for free by @freeCodeCamp
freecodecamp.org/learn/scientif…
That's it for this tread 👋

A retweet for the first one would really mean a lot 🙏

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More from @PiyalBanik

11 Jul
Here are this week's Data Science Interview Questions along with the correct answer

Thread 🧵👇

#MachineLearning #Python #100DaysOfCode
Answer by @josh_ko_naman

1) SL has a feedback mechanism.
UL has no feedback mechanism.

2) Supervised learning involves building a model for predicting, or estimating.
In unsupervised learning, we can learn relationships and structures from data

Answer by @ammaryh92 & @arunkumarai

-regularization
-simpler model architecture
-more training data
-reduce noise in the data
-reduce the number of input attributes
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3 Jul
Want to learn Data Science but confused about where to start and what to follow?

Here are the ultimate 12 months Learning path to becoming a Data Scientist 👨‍🎓

Note: I'm personally following this roadmap

🧵👇

#DataScience #MachineLearning #100DaysOfCode #66DaysOfCode #Python
Since we're currently in July, so start from this month.

Understanding Data Science and getting started with Python
- what is data science?
- what does a data scientist do?
- find out various resources
- Set up the system
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- Introduction to Pandas & Numpy
August -

Mathematics, Statistics & SQL
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- SQL for Data science
- Projects on EDA and SQL

Start engaging in the Data Science & Machine Learning community
Read 14 tweets
2 Jul
Best Data Science blogs to follow in 2021

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1. Towards Data Science

TDS is a Medium publication having audience-oriented content about Data Science, along with blogs on related fields such as Machine Learning, Programming, Visualization, and Artificial Intelligence.

towardsdatascience.com
2. Data Science Central

DSC is one of the leading repositories of Data Science content that is regularly updated with the latest trends across domains such as Artificial Intelligence, Machine Learning, Deep Learning, Analytics, Big Data, and much more.

datasciencecentral.com
Read 9 tweets
1 Jul
NumPy 🔥

It is a Linear Algebra Library for #Python, the reason it is so important for Data Science is that almost all of the libraries in the PyData Ecosystem rely on NumPy as one of their main building blocks👨‍🏫.

Here's everything you need🧵👇

#DataScience #100DaysOfCode
1⃣Numpy Arrays

NumPy arrays are the main way we use Numpy. Numpy arrays essentially come in two flavors: vectors and matrices. Vectors are strictly 1-d arrays and matrices are 2-d (but you should note a matrix can still have only one row or one column). Image
2⃣Built-in Methods

There are lots of built-in ways to generate Arrays
- zeros
- ones
- eye
- arange
- linspace Image
Read 11 tweets
19 Jun
Ever wondered how a Data Scientist thinks about a problem? Here are the major steps involved in tackling a data science problem.

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#DataScience #MachineLearning #100DaysOfCode
1. Business Understanding: We should have clarity of what is the exact problem we are going to solve.

What is the problem that we are trying to solve? - Asking the right questions as a Data Scientist starts with understanding the goal of the business.
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- Descriptive
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and it indicates the necessary data content, formats, and sources to be gathered
Read 12 tweets
18 Jun
Top 7 interesting careers related to Data Science to explore. Pick one and start learning.

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#DataScience #ArtificialIntelligence #MachineLearning #BigData
1. Data Scientist

Data scientist use their analytical and technical capabilities to extract meaningful insight from data.
2. Machine Learning Engineer

Machine Learning engineer's final output is the working software, and their audience for this output consists of other software components that run automatically with minimal human supervision. The decisions are made by machines.
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