Python for Data Science
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Are you ready to take the next leap in your journey to become a Data Scientist?
This hands-on course is designed for absolute beginners as well as for proficient programmers who want to use the Python for solving real life problems. You will learn how analyse data, make interesting data visualisations, drive insights, scrape web, automate boring tasks and working with databases using SQL.
Data Science has one of the most rewarding jobs of the 21st century and fortune-500 tech companies are spending heavily on data scientists! Data Science as a career is very rewarding and offers one of the highest salaries in the world. This course is designed for both beginners with some programming experience or experienced developers looking to enter the world of Data Science!
This comprehensive course is taught by Mohit Uniyal, who is a popular Data Science Bootcamp instructor in India and has taught thousands of students in several online and in-person courses over last 3+ years. This course is worth thousands of dollars, but Coding Minutes is providing you this course to you at a fraction of its original cost! This is action oriented course, we not just delve into theory but focus on the practical aspects by building 5 projects. With over 150+ High Quality video lectures, easy to understand explanations and complete code repository this is one of the most detailed and robust course for learning data science.
The course starts with basics of Python and then diving deeper into data science topics! Here are some of the topics that you will learn in this course.
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Programming with Python
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Numeric Computation using NumPy
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Data Analysis using Pandas
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Data Visualisation using Matplotlib
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Data Visualisation using Seaborn
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Fetching data from Web API’s
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Data Acquisition
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Web Scraping using Beautiful Soup
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Building a Web Crawler using Scrapy
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Automating boring stuff using Selenium
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Language of Databases – SQL!
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Introduction to Machine Learning
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and much, much more!
Sign up for the course and take your first step towards becoming a data science engineer! See you in the course!
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8
Print, Variable and DatatypesLearn about the print function, how to create variables, and different data types in python
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9
Input in Python
Learn how to take input from the user
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10
Operators in Python
Learn about the different types of operators in python
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11
Conditional Statements
Students will learn about control flow : if , else, elif
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12
Loops and Iterations
We will walk you through an example of avoiding repetition of the code using Loops.
Specifically while loop and for loop
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13
Break and Continue
In this lecture, we discuss 2 special keywords: break and continue, and their usage.
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Odd Vs. Even -
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Largest Number
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Factorial of a Number
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17
Prime Numbers
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18
Python Fundamental Quiz
This is the first Quiz to test your knowledge on Python Fundamentals
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19
Strings
Learn about the string and its properties.
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20
String Functions
Students will learn some important functions associated with the strings
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21
Palindrome Strings
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22
Count Vowels
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23
Lists
Students will learn about the list and its usage.
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List Comprehension
Learn How to write small code for list iteration using list comprehension
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Second Largest Element
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26
No Duplicacy
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27
Tuples
Learn how to create tuples and how tuples are different from lists.
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28
Sets
Learn about the unique property of Sets Data Structure and solve a coding question.
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29
Dictionaries
Students will learn how to represent a tabular type of data in python. (HashMap)
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30
Reverse a Dictionary
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31
Most Frequent
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32
Pythion In-Built Data Structures Quiz
This quiz tests your data structures understanding in Python
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33
Function Introduction
Learn basic of functions, creating functions in python
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34
Default Arguments in Functions
Learn about the default arguments you can provide to your functions.
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35
Args and kwargs
Students will get to know about the args and kwargs arguments in functions.
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36
In-built Functions
Learn about different in-built functions like abs, round, map, filter etc...
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37
Print Pattern
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38
Prime Numbes - II
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39
What are Python Modules?
Here, We'll discuss about the python In built. modules.
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40
Custom Modules
Learn to create your own modules in python.
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41
What is __name__ == '__main__' ?
Learn __name__ property of a module. and why __name__ == '__main__'
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42
Python Functions and Modules Quiz
this is a quick mcq to test your functions and modules understanding.
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43
OOPS : Classes and Objects
Students will learn about fundaments of classes and objects
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44
Constructors
Learn about the constructor of a class.
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Instance Methods
Learn to create a method associated with an instance.
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Class Variables
Understand the importance of class variables and how to create class variables.
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47
Add die() method
add die method to the Human class.
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48
Magic Functions
Learn about the magic functions or dunder functions.
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49
Inheritance
We will discuss about inheritance.
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50
Add kill() method
We'll add kill() method to the Hitman class
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51
Polymorphism
We'll create different functionality of introduce method for Hitman using polymorphism and function overriding.
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52
OOPs Test
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53
Python OOPs Quiz
Quiz to test your knowledge on OOPs
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54
What is Data ?
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55
What is Statistics & Probability
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Population Vs Sample
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Types of Statistics
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Mean, Mode, Median
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Range, Variance, Deviation
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60
Histograms
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61
Normal Distribution
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Standardization
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63
Marginal, Joint and Conditional Probability
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64
Questions on Probability
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65
Bayes Theorem
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66
Why Numpy?
learn why numpy is used in data science world.
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67
Numpy Arrays
learn about the most fundament entity in numpy i.e arrays
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68
Special Arrays in Numpy
learn few special functions to create special arrays like ones, zeros, identity etc.
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Indexing and Masking
learn about the array indexing, slicing, and boolean masking in arrays
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70
Basic Operations in Numpy Arrays
We'll discuss some operations related to the NumPy arrays
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71
More Operations in Arrays
This lecture is in the continuation of the last lecture.
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72
Shape Manipulation
learn to change the shapes of arrays with reshaping and stacking
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73
Broadcasting
Broadcasting is an important phenomenon in NumPy array operations
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74
Vectorisation
Vectorisation is one of the key reasons why NumPy operations are fast. We'll discuss this strategy.
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75
Numpy Assignment
solve the numpy questions.
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76
Quiz Time : NumPy
this quiz checks your understanding of numpy.
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77
Padded Matrix
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78
Pandas Introduction and Series
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79
Introduction to DataFrames
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Indexing in DataFrames
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81
Masking and Boolean Indexing
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Iris Dataset
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Grouping Data
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Handling Missing Data
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Concatenate DataFrames
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Merging DataFrames
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Output Files
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Pandas Assignment
solve pandas questions.
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Quiz Time : Pandas
pandas quiz to test your skills
