Unsinkable: Data Science with Python
4.7 (14 ratings)
Instead of using a simple lifetime average, Udemy calculates a course's star rating by considering a number of different factors such as the number of ratings, the age of ratings, and the likelihood of fraudulent ratings.
120 students enrolled
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Unsinkable: Data Science with Python

Start Building Your Data Science Portfolio
4.7 (14 ratings)
Instead of using a simple lifetime average, Udemy calculates a course's star rating by considering a number of different factors such as the number of ratings, the age of ratings, and the likelihood of fraudulent ratings.
120 students enrolled
Last updated 7/2017
English
Price: $50
30-Day Money-Back Guarantee
Includes:
  • 9 hours on-demand video
  • 3 Supplemental Resources
  • Full lifetime access
  • Access on mobile and TV
  • Assignments
  • Certificate of Completion
What Will I Learn?
  • Use Python and its various libraries to analyse data and gather inferences from it.
  • Have a starter portfolio of projects to demonstrate their technical capabilities.
  • Understand how to visualise Data
  • Know how to use Numpy and Pandas
View Curriculum
Requirements
  • High school mathematics and statistics
  • Python 3 with Jupyter Notebooks Installed
  • Access to the internet
Description

Unsinkable - because there is no "Titanic" dataset in here! Only what's relevant to a student learning data science, and we use Real World data sets as much as possible. 

In this course, we will set out to learn Python and use it to gain an understanding of the basic principles of Data Science. Not only will we cover the basics, we will also tackle some real world problems, and begin the journey to create a Data Science portfolio. 

Who is the target audience?
  • This course is for students and professionals who wish to learn the basics of Data Analysis using Python.
  • Students who wish to start creating a Data Science Portfolio of Projects
Compare to Other Data Science Courses
Curriculum For This Course
68 Lectures
09:10:42
+
Unix and Shell Command Basics
4 Lectures 29:14

Unix - 2
07:39

Unix - 3
11:04

Unix and Shell Command Basics - On Windows
01:29
+
Python Basics
6 Lectures 29:04

Your very first program in Python. 

Preview 02:33

Let's test your understanding of the 'print' statement.

Python Basics
1 question


Python - Comments
05:47

Adding comments to your codebase.

Comments
2 questions

Python - Mathematical Operations
03:09

Testing your knowledge of mathematical operations in Python

Mathematical Operations
1 question

Python - Words and Numbers
04:15

Python - Assignment Operations
11:04

Test your ability to assign a value to a variable

Assigning Values
1 question
+
All About Numbers
4 Lectures 16:37
Integers and Floats
08:57

Converting Between Types
02:13

Revisiting a few Mathematical Operations
02:17

Equality and Comparison Operators
03:10
+
Strings
4 Lectures 45:30
Strings - 1
13:20


Test your knowledge of strings in Python

Strings
3 questions

Strings - 3
10:38

Test your knowledge of String Operations

String Operations
1 question

Strings - 4
11:09
+
Booleans
1 Lecture 07:16
Booleans
07:16

Test your understanding of Booleans

Booleans
2 questions
+
Collections - Lists, Tuples, Sets, Dictionaries
4 Lectures 30:53
Sets
05:35


Tuples
04:17

Dictionaries
07:46
+
Loops and Automation
5 Lectures 58:12
Control Flow
14:36

Loops
12:32

Range
08:12

Break and Continue
04:50

+
Let it Function!
3 Lectures 28:54
Inbuilt Functions
08:33

Functions from Libraries
09:02

User Defined Functions
11:19
+
Reading and Writing Files
1 Lecture 11:37
Read/Write Files
11:37
+
Visualise This!
7 Lectures 38:45
Introduction to Data Viz
03:44

Matplotlib Reference
03:06

Line Plots
08:54

Bar Plots
03:03

Histograms
04:24

Scatterplots
05:49

4 More Sections
About the Instructor
Prasant Sudhakaran
4.7 Average rating
14 Reviews
120 Students
1 Course
Data Scientist, Investor

I am a Data Scientist, with an extensive background using Machine Learning/Artificial Intelligence in the Capital Markets. Starting my career in Banking, followed by Management Consulting, I have worked across domains, and firms ranging from Fortune 50 firms to not-for-profits.
The tools I use on a daily basis include R, Python, SQL and MongoDB, and at times a graph database such as Neo4j. 

Some of my analysis has been published in leading media outlets such as CNBC. Aside from Data Science, I am very passionate about Finance, Strategy, Early Stage Venture Capital, and reading about medieval warfare.