4.25 (517 reviews)
☑ Install and Get Started With the Python Data Science Environment- Jupyter/iPython
☑ Read In Data Into The Jupiter/iPython Environment From Different Sources
☑ Carry Out Basic Data Pre-processing & Wrangling In the Jupyter Environment
☑ Learn to IDENTIFY Which Visualisations Should be Used in ANY given Situation
☑ Go From A Basic Level To Performing Some Of The MOST COMMON Data Preprocessing, Data Wrangling & Data Visualization Tasks In Jupyter
☑ How To Use Some Of The MOST IMPORTANT Data Wrangling & Visualisation Packages Such As Matplotlib
☑ Build POWERFUL Visualisations and Graphs from REAL DATA
☑ Apply Data Visualization Concepts For PRACTICAL Data Analysis & Interpretation
☑ Gain PROFICIENCY In Data Preprocessing, Data Wrangling & Data Visualisation In Jupyter By Putting Your Soon-To-Be-Acquired Knowledge Into IMMEDIATE Application
Hello, My name is Minerva Singh and I am an Oxford University MPhil (Geography and Environment) graduate. I recently finished a PhD at Cambridge University (Tropical Ecology and Conservation).
I have several years of experience in analyzing real life data from different sources using statistical modeling and producing publications for international peer reviewed journals. If you find statistics books & manuals too vague, expensive & not practical, then you’re going to love this course!
I created this course to take you by hand and teach you all the concepts, and tackle the most fundamental building block on practical data science- data wrangling and visualisation.
GET ACCESS TO A COURSE THAT IS JAM PACKED WITH TONS OF APPLICABLE INFORMATION!
This course is your sure-fire way of acquiring the knowledge and statistical data analysis wrangling and visualisation skills that I acquired from the rigorous training I received at 2 of the best universities in the world, perusal of numerous books and publishing statistically rich papers in renowned international journal like PLOS One.
To be more specific, here’s what the course will do for you:
(a) It will take you (even if you have no prior statistical modelling/analysis background) from a basic level to performing some of the most common data wrangling tasks in Python.
(b) It will equip you to use some of the most important Python data wrangling and visualisation packages such as seaborn.
(c) It will Introduce some of the most important data visualisation concepts to you in a practical manner such that you can apply these concepts for practical data analysis and interpretation.
(d) You will also be able to decide which wrangling and visualisation techniques are best suited to answer your research questions and applicable to your data and interpret the results.
The course will mostly focus on helping you implement different techniques on real-life data such as Olympic and Nobel Prize winners
After each video you will learn a new concept or technique which you may apply to your own projects immediately! Reinforce your knowledge through practical quizzes and assignments.
TAKE ACTION NOW :) You’ll also have my continuous support when you take this course just to make sure you’re successful with it. If my GUARANTEE is not enough for you, you can ask for a refund within 30 days of your purchase in case you’re not completely satisfied with the course.
TAKE ACTION TODAY! I will personally support you and ensure your experience with this course is a success.
INTRODUCTION TO THE COURSE: The Key Concepts and Software Tools
Welcome to the Course
Data & Script For the Course
Python Data Science Environment
For Mac Users
Introduction to IPython/Jupyter
ipython in Browser
Read in Data From Different Sources With Pandas
What are Pandas?
Read CSV Data
Read Excel Data
Read in HTML Data
Remove NA Values
Missing Values in a Real Dataset
Imputing Qualitative Values
Use k-NN for Data Imputation
Basic Data Wrangling
Preliminary Data Explorations
Basic Data Handling With Conditional Statements
Change Column Name
Change the Column Type
Explore Date Related Data
Simple Date Related Computations
More Data Wrangling
Data Subsetting and Indexing
More Data Subsetting
Extract Information From Strings
(Fuzzy) String Matching
Ranking & Sorting
Merging and Joining
Feature Selection and Transformation
Using Correlation to Decide Which Features to Retain
Univariate Feature Selection
Recursive Feature Elimination (RFE)
Theory Behind PCA
Create a New Feature
Theory Behind Data Visualisation
What is Data Visualisation?
Some Theoretical Principles Behind Data Visualisation
Most Common Data Visualizations
Histograms-Visualize the Distribution of Continuous Numerical Variables
Boxplots-Visualize the Distribution of Continuous Numerical Variables
Scatter plot-Relationship Between Two Numerical Variables
More Line Charts
Some More Plot Types
And Some More
Using Colabs as an Online Jupyter Notebook
It was a fascinating subject and a good collection of topics, unfortunately, very poor delivery. - excellent overview to demonstrate what is possible but not a course - errors that come out during lectures were left unexplained poor quality of resources, missing source files or incorrect content inside - most of the times we were showed how to do things without any explanation on why we do it this way
Found the content very relevant . . note that the curriculum did seem a little rushed since it is a crash course. But overall, found it very useful to build a foundation on.
This course is one of the most structured course for anyone who is willing to learn. This is must for all who wants to learn at a fast yet do not want miss important topics.
Amazing course, to begin with, teaches all essential basics of data visualization with python required to grasp the essence of programming and above all it teaches some real application which is amazing.
One of the worst tutorial I ever watched. Presentation skill is ZERO, not doing anything practical just reading already typed code. :(
The course was informative and really good especially for a beginner with some programming background !
I just started learning data wrangling and data visualization. The step by step short tutorials are very helpful to understand. All the sections were intuitive and the resources are very much useful! Enjoyed and more confident about my skills now!
absolutely fantastic. I feel like I've learn so much during this course and it answered many of my questions regarding Python .
A very well-explained and practical course of data wrangling and visualization. The whole course was very interesting and knowledgeable for every python beginner like me. Sessions, resources are phenomenal!
Good course covering almost all the Data Wrangling & Data Visualization with python.Very good for beginners. A good mix of theory and practical. Overall I am totally satisfied!
A great course to learn Data Wrangling & Data Visualization! I love the quick summary of each section. The quality of resources here is amazing.
This is one of the best courses I have completed about Data Wrangling & Data Visualization. The lectures were very informative and each steps of code were explained very clearly.A big thumbs up to the instructor!
Really helpful course! Very organized sessions and resources. Learned so much from it. Data Wrangling & Data Visualization course wouldn't be so enjoyable without python!
Course material needs updating, from the Initial download file anyway. Still its a good intro to data wrangling with python.
The instructor is not clear about what she is teaching, often she does not even complete her sentences. There are a couple of codes along the course that does not work when she introduces it, but she keeps on going as it did. Her explanations are extremely poor on the topic. There is no theoretical explanation for the statistical tools she introduces in this course. VERY POOR COURSE IN EVERY LITTLE ASPECT OF IT!! Not sure about her other courses in this platform, but this one is really bad.