Python for Data Science - Part 1 | FestMan Learning Hub

COURSE INTRODUCTION

5 Parts - 0:12 Hr

Course Overview

Course overview

4 Min

Attachments:

Introduction

Course overview

3 Min

Attachments:

Learning Objectives

Course objectives

3 Min

Attachments:

How to get certified

How to receive your certificate.

2 Min

Attachments:

Exercise Files

Download the exercise files and follow along with the videos. We learn best through practicing. Make use of the exercise files and develop your hands-on skills.

14.74 KB MB

INTRODUCTION TO GOOGLE COLAB

2 Parts - 0:01 Hr

Introduction to Colab

What is Colab Notebooks

1 Min

Attachments:

Introduction to Google Colab

13.15 MB MB

Python Basics

11 Parts - 0:03 Hr

What is Python

5.57 MB MB

Why do you need to learn Python

6.80 MB MB

Why Python is popular

5.30 MB MB

Application of Python

7.77 MB MB

Live sample code

Access the live code on Google colab

1 Min

Attachments:

Python operators

10.79 MB MB

Python Data types

7.79 MB MB

Type Conversion

12.71 MB MB

Adding comments

9.43 MB MB

Using variable

In Python we assign values to variables using the assignment operator(=).

2 Min

Attachments:

Python strings

String
Strings in Python are shown as the variable type str. You can define a string with either double quotation marks " or quotation marks '.

String Methods
Python has a set of built-in methods that you can use on strings. Some of the methods include:

Len(): Count the number of charters in a string
upper(): Converts a string into upper case
lower(): Converts string into lowercase
capitalize(): Converts the first character to upper case
title(): Converts the first character of each word to upper case
format(): Formats specified values in a string
count() : Returns the number of times a specified value occurs in a string
split(): Splits the string at the specified separator, and returns a list

19.36 MB MB

WORKING WITH PYTHON DATA STRUCTURES

1 Parts

Introduction to Data Structures

Python Data Structures
Python’s data structures are simple but powerful. Mastering their use is a critical part of becoming a proficient Python programmer. These are some of the data structures in Python:

Tuples
Lists
Dictionaries
Dataframes and Series
Sets

3.95 MB MB

Python List

9 Parts - 0:22 Hr

Live Code

Access the sample live notebook for practice.

5 Min

Attachments:

Introduction to Lists

3.98 MB MB

Creating Lists

13.76 MB MB

Accessing lists elements

16.12 MB MB

Updating lists

7.26 MB MB

List methods

Introduction to List methods

5 Min

Attachments:

List Methods

12.80 MB MB

List Functions

Python List functions

2 Min

Attachments:

Live Exercise

Test your skills

10 Min

Attachments:

Tuples

4 Parts - 0:05 Hr

Live code

Exercise workbook

5 Min

Attachments:

Creating Tuples

10.07 MB MB

Accessing Items

13.31 MB MB

Unpack tuples

11.93 MB MB

PYTHON DICTIONARY

5 Parts - 0:02 Hr

Live code

Sample exercise code

2 Min

Attachments:

Introduction to Python Dictionaries

20.86 MB MB

Updating Dictionary

16.30 MB MB

Dictionary Methods and Functions

Python Dictionary Methods
Python has a set of built-in methods that you can use on dictionaries.

clear( ) - Removes all the elements from the dictionary
get( ) - Returns the value of the specified key
items( ) - Returns a list containing a tuple for each key value pair
keys( ) - Returns a list containing the dictionary's keys
pop( ) - Removes the element with the specified key
popitem( ) - Removes the last inserted key-value pair
update( )- Updates the dictionary with the specified key-value pairs
values( ) - Returns a list of all the values in the dictionary

16.04 MB MB

Dictionary Functions

29.23 MB MB

CONDITIONAL STATEMENTS

7 Parts - 0:12 Hr

Sample Notebook

Sample Notebook for practice

2 Min

Attachments:

Introduction to IF Statements

Introduction to IF Statement

10 Min

Attachments:

IF Statements Demos

26.19 MB MB

IF Statements Demos 2

16.17 MB MB

Introduction to ELSE Clause

6.42 MB MB

ELSE Clause Demo

23.38 MB MB

ELIF Clause

38.01 MB MB

LOOPS

18 Parts - 0:10 Hr

Sample Notebook

10 Min

Attachments:

Introduction to Loops

5.15 MB MB

Introduction to for loops demo 1

9.29 MB MB

Introduction to for loops demo 2

11.89 MB MB

Introduction to for loops demo 3

10.43 MB MB

Introduction to for loops demo 4

19.43 MB MB

Introduction to for loops demo 5

11.16 MB MB

Iterating over dictionaries

16.11 MB MB

Introduction to Nested Loops

24.99 MB MB

Nested Loops

16.74 MB MB

Introduction to Loops with IF Statement

21.39 MB MB

Iterating over dictionaries with IF Statement

13.54 MB MB

Introduction to WHILE Loops

11.39 MB MB

While loops demo 1

10.08 MB MB

While loops demo 2

6.47 MB MB

List comprehension

15.16 MB MB

Enumerate Function

15.33 MB MB

Designing Login system

46.41 MB MB

FUNCTIONS

9 Parts - 0:05 Hr

Sample Notebook

Notebook for practice

5 Min

Attachments:

Introduction to Functions

6.05 MB MB

User defined function_No input

9.41 MB MB

User defined function_Single Input

14.72 MB MB

User defined function_Multiple Input

13.88 MB MB

User Defined Function_Demo 1

10.65 MB MB

User Defined Function_Demo 2

14.27 MB MB

Function Documentation

13.12 MB MB

The MAP Function

7.22 MB MB

PYTHON PACKAGES

1 Parts - 0:02 Hr

Introduction to Packages or Libraries

Python packages

2 Min

Attachments:

WORKING WITH NUMPY ARRAYS

18 Parts - 0:07 Hr

Sample Notebook

Notebook

5 Min

Attachments:

Introduction to Arrays

6.37 MB MB

Arrays vs Lists

6.20 MB MB

Creating Arrays

17.39 MB MB

Creating multidimensional arrays

17.27 MB MB

Creating 3 dimensional arrays

14.30 MB MB

Data types

14.36 MB MB

Reshaping arrays

23.18 MB MB

Resize arrays

9.55 MB MB

Indexing arrays

13.10 MB MB

Slicing arrays

16.92 MB MB

Slicing multi dimensional arrays

23.30 MB MB

Vectorization

16.57 MB MB

Basic Numpy operations

18.28 MB MB

Aggregate functions

11.77 MB MB

Aggregate functions and arrays

15.47 MB MB

Mini Project

24.68 MB MB

Course review and certificate

Course review

2 Min

Attachments:

Zion Bonzo Student

27 Sep 2023 | 14:46

I just finished taking the Python Introduction course on Festman Learning Hub, and it was a fantastic experience! The course thoroughly introduced Python basics, such as lists, tuples, loops, functions, and numpy. The instructor was engaging, and the material was presented clearly and concisely. The hands-on exercises were beneficial, as they allowed me to apply what I had learned in real-world situations. I highly recommend this course to anyone interested in learning Python basics and establishing a solid foundation in this powerful programming language.
I am looking forward to the Part 2 on Pandas.