Complete Data Wrangling & Data Visualisation With Python (Udemy.com)
Learn to Preprocess, Wrangle and Visualise Data For Practical Data Science Applications in Python
Created by: Minerva Singh
Last updated November 2025
What you will learn
- 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
How it compares
Against the other 388 rated Udemy courses in Python on CourseDuck:
- Rating4.3 out of 5higher than 25% of them
- Reviews1,186#171 of 389 by number of reviews
- Length6.5 hoursshorter than 62% of them
- Last updatedNovember 2025more recently than 72% of them
Course Description
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.
Instructor Details
- 4.3 Rating
1,186 Reviews
Minerva Singh
I completed a PhD (University of Cambridge, UK) in 2017 where I focussed on implementing data science techniques for quantifying the impact of forest loss on tropical ecosystems. I hold an MPhil (School of Geography and Environment) and an MSc (Department of Engineering) from Oxford University. I have more than 10 year's experience in conducting academic research (published in high level peer-reviewed international scientific journals such as PLOS One) and advising both non-governmental and industry stakeholders in data science, deep learning and earth observation (EO) related topics.
I have a strong track record in implementing machine learning, data visualization, spatial data analysis, deep learning and natural language processing tasks using both R and Python. In addition to being educated at the best universities in the world, I have honed my statistical and data analysis skills through many MOOCs, including The Analytics Edge (R based statistics and machine learning course offered by EdX), Statistical Learning (R-based Machine Learning course offered by Stanford online) and the IBM Data Science Professional certificate Track. I specialise in a variety of topics ranging from deep learning (Tensorflow, Keras) to machine learning to spatial data analysis (including EO data processing), data visualizations, natural language processing, financial analysis among others. I have acted as a peer reviewer on highly
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Reviews
By Ramon Casals Simó on 12/5/2023
Esperaba una mejor explicación de los conceptos que aplican a este ámbito, cuesta entender muchos ejemplos prácticos sin este contexto un poco más teórico. Y el material del curso (código python y ficheros de datos) está incompleto y desordenado: faltan tanto ficheros de código, como de datos, y algunos ficheros no están en la sección que corresponde.
By Carlos Elgado on 10/10/2022
I like that the instructor is starting slow and making sure people are comfortable with the environment we will be working in: Anaconda. I also like that she shows multiple ways to access what we need. There are a number of errors in the Jupyter notebooks and files as well as several "mis-speaks" including the instructor saying she is subsetting the first seven columns and she instead subsets the second through eighth column. Also the "NFA 2018.csv" is missing from the "Data and Code" zip file. I was able to find it online and successfully use it but it would be nice if it was in the code download.
By Raveena Sarkar on 11/7/2021
The course contains valuable information about processing,wrangling and visualising data for data science applications in Python. the concept has immense potential for practical applications. The instructor is very clear and impressive in explaining various aspects of the concept.
By Ravi Srivastava on 9/26/2021
The course contains valuable information about the utility of various tool with respect to their applicability in Python. The concept has vast opportunities for practical usage. The instructor has complete knowledge of the subject and her delivery is impressive.
By Rajesh Kumar on 7/13/2021
Complete data wrangling and data visualisation with python is a complete course where the concept has been explained unambiguously. My knowledge of the subject has certainly enriched.The instructor's thought process and delivery is very clear and appealing.
By Mukund Pandey on 10/26/2020
I see as the course moves forward, it has something good to see but still i see examples are less and less hard one actually, because most of the pattern showed in the course, are very basic and self explanatory.
By Nafila Tarannum on 8/20/2020
An excellent course for those who want to boost their abilities about data wrangling and visualization using Python. It tackles diverse and challenging problems, for you to practice and round out every concept. Highly recommended!
By Ama Akar on 8/18/2020
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
By Yuvraj Alim on 8/15/2020
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.
By Kiba Lovren on 8/12/2020
The explanations are clear and the code is very efficient. I've learnt so much. Highly recommended.
By Chinki Munni on 8/11/2020
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.
By Raj Sharma on 8/8/2020
Very nice instructor, I always enjoyed the videos and it was a lot of fun! Every lectures were easy and a great opportunity to learn! Will definitely recommend this course :) Thank you
Quality Score
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Overall Score : 86 / 100









