Are you ready to start your path to becoming a data manipulation and visualization expert?
Do you know nothing about data manipulation and visualization but want to know them well enough so that you can implement projects?
Are you worried that learning data manipulation and visualization is going to be tough?
Do you ever wonder if Data Scientists having a good understanding of data manipulation and visualization have a bright future?
Listen to what the most relevant people have to say:
- “Data Science will automate jobs that most people thought could only be done by people.” ~ Dave Waters
- “Just as electricity transformed almost everything 100 years ago, today, I actually have a hard time thinking of an industry that I don’t think Artificial Intelligence/Data Science will transform in the next several years.” ~Andrew Ng
- “A breakthrough in Data Science would be worth ten MicroSofts.” ~ Bill Gates
Data is, without a doubt, the new electricity. Over the next several years, data is going to transform everything. And guess what? Data manipulation and visualization skills are at the core of Data Science.
There are lots of courses and lectures out there regarding data manipulation and visualization. But this course is different!
This course follows a step-by-step and straightforward methodology. In every new tutorial, you will build on what you have already learned and move one extra step forward. You are then assigned a small task that you solve at the beginning of the next video.
You start by first learning the theoretical part of a data visualization concept. Then, you implement everything practically, using Python. We are using Python as a programming language because it has a lot of demand in the market. Plus, it is a super easy and efficient language. Python is the hottest programming language nowadays if we talk about machine learning or data science, and thus for data manipulation and visualization.
You don’t need to worry if you don’t know Python. We have a course for absolute beginners on our channel as well. And by the way, you need not know a lot of Python for this course. You will explore packages and will rely mostly on one-liners as compared to lengthy codes.
You will also implement a lot of mini projects in live coding sessions in which you will gain a complete look and feel on how to implement modules in data manipulation and visualization.
With over 12 hours of HD video lectures divided into 75+ small videos and detailed code notebooks for every lecture, this is one of the most comprehensive courses for data manipulation and visualization on Udemy!
You’ll not only learn how to solve problems in data manipulation and visualization, but you will also be equipped with the right tools in your hand!
Who is this course for?
- This course is for you if you know nothing about data manipulation and visualization.
- This course is for you if you are tired of data manipulation and visualization courses that are too complicated and expensive.
- This course is for you if a step-by-step and straightforward methodology of teaching appeals to you.
- This course is for you if you want to learn data manipulation and visualization practically.
- This course is for you if you want to learn data manipulation and visualization right from the beginning.
- This course is for you if you want to implement a lot of mini projects in live coding sessions.
- This course is for you if you are curious to learn about the theory of data manipulation and visualization and then implement it in real-world projects.
- The importance of data manipulation and visualization in Data Science
- How to manage text data with strings
- Useful string methods and indexing techniques
- The use of multiline strings and escape sequences
- The basics of Data Structures in Python
- CRUD operations on Data Structures (Create, Retrieve, Update, Delete)
- How does Python manage memory for data structures (Deep copy vs. Shallow copy)
- The importance of the NumPy package
- The concepts of multidimensional arrays in NumPy
- Useful modules in NumPy including Random
- The concepts of slicing in NumPy
- The difference between masking and slicing in NumPy
- The concepts of broadcasting of variables in NumPy
- Useful functions and operators in NumPy
- The importance of universal functions in NumPy
- How to process images using NumPy
- How to build complicated applications like KNN with a few lines of codes in NumPy
- The concept of structured arrays in NumPy
- The importance of Pandas package in Python
- The series object in Pandas and its resemblance to NumPy arrays
- The spreadsheet-like data object: DataFrame in Pandas
- Indexing and slicing in Pandas
- Handling missing values in data files
- The difference between implicit and explicit indices in Pandas
- Process a real data file using Pandas
- Hierarchical indexing in Pandas
- Useful functions in Pandas
- The concepts of pivot tables in Pandas
- How to work with time-series data
- Process Covid-19 real data file using Pandas
- The basics of visualization using Matplotlib
- The different plotting styles and colors in Matplotlib
- Multiple plots on the same figure using Matplotlib
- Subplots in the same figure using Matplotlib
- Annotating the figures using texts, labels, legends using Matplotlib
- Axis management in Matplotlib
- Histograms and filled contours in Matplotlib
- 3D visualizations in Matplotlib
- The importance of Seaborn
- Styles and aesthetics in Seaborn
- Scatter plots in Seaborn
- Categorical data plots in Seaborn
- Facets and heatmaps in Seaborn
- Interactive visualizations in Bokeh
- Multiple plots in Bokeh
- Grid plots in Bokeh
- 3D interactive visualizations using Plotly
- Surface and scatter 3D interactive plots in Plotly
- Geographic mapping using folium
- Implement COVID-19 density over the globe
- Plotting directly in Pandas
- Absolutely no prior knowledge or experience needed. You only need a passion to be successful!
- You can be a beginner in data science, or you can be proficient in it.
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