Plots In R Ggplot2 Courses
Power Bi, Dax, Table, Excel, Statistics, Data visualization, BI, Business Intelligence, Statistical practices with Excel
Rating: 5
Learn how to use Excel for Data Visualization and Business Intelligence
Rating: 5
Metaverse, Blockchain, Investment, NFT, Digital wallet, Digital ID, VR, AR, Digital Twin: Future is here
Rating: 5
Students will learn how to write a screenplay from scratch in a professional way: Screenwriting & Filmmaking
Rating: 5
Generate summary statistics quickly and extend that with in depth summaries for all of your data analysis projects
Rating: 5
Quality Control, MS Excel, Experimental Analysis, Useful for Quality Engineers.
Rating: 5
Skills to improve your CFD results
Rating: 4.92
A course for learning the basics of Tableau, that is relevant to football/soccer
Rating: 4.83333
Learn Layer, Blocks, Parametric Feature, Planning, Plotting, Layout, Isometric Drawing, 3D-Civil/Mechanical/Architecture
Rating: 4.8
Be an expert of analyzing AC Circuits. This course will you a huge understanding of how AC circuits work.
Rating: 4.8
30 Creative writing exercises. Writing to improve creative thinking. Write to make an income from your creative writing.
Rating: 4.8
Build Real World Microsoft Power BI Desktop Projects. In This Course Learn Business Intelligence, Data Analysis.
Rating: 4.75926
Python Plotting with Seaborn for Beginners in Data Science, Machine Learning and Deep Learning
Rating: 4.75
The indispensable guide to creating a novel that leaves your readers saying, "I couldn't put it down!"
Rating: 4.72807
A life changing course designed to give you the tools to get you healthy through growing and eating organic food.
Rating: 4.72727
Learn to design amazing charts for visualization and communication for [data] science, journalism and storytelling
Rating: 4.71127
Learn how to make frequency response and impedance measurements and set up the foundation for designing crossovers.
Rating: 4.70588
Introduction to fundamentals of R programming - Writing effective, simple, and modern R codes using tidyverse and more
Rating: 4.7
Learn Tableau for Data Science step-by-step. Real-Life Data Analytics Exercises & Quizzes Included. Learn by doing!
Rating: 4.7
Fundamental Principles, Cool Graphs & Charts in Python
Rating: 4.7
Visualize data using pandas, matplotlib and seaborn libraries for data analysis and data science
Rating: 4.68919
Learn everything from Probability & Statistics, then test your knowledge with 600+ practice questions
Rating: 4.67225
R Programming course suitable for everyone, no coding experience or a statistics background needed
Rating: 4.65736
A course for anyone who is interested in quickly improving their data analysis skills. Experienced or new will benefit.
Rating: 4.65
Become an Excel Data Visualization Expert and Explore all impressive visualization Techniques in Excel
Rating: 4.65
Learn to use the FREE Space on Your Hard Drive to earn passive income from Crypto Farming at home!
Rating: 4.65
Get a kick start on exploratory data analysis using plotly library
Rating: 4.65
Learn how to use R and Shiny to create compelling data visualizations and how to share them online.
Rating: 4.63333
Learn how easy it is to use Python to do your biostatistical analysis
Rating: 4.625
Learn how to use Python and Pandas for data analysis and data manipulation. Transform, clean and merge data with Python.
Rating: 4.62037
[2022] Build 30+ ML Projects in 30 Days in AWS, Master SageMaker JumpStart, Canvas, AutoPilot, DataWrangler, Lambda & S3
Rating: 4.61594
Learn the skills to write engaging fiction, develop your voice, and become the successful writer you want to be!
Rating: 4.61111
Just 15 days to master Power BI Desktop + Power BI Service (Cloud) + Power BI Mobile in a project-based, practical way.
Rating: 4.61053
A complete guide on creating beautiful plots and data dashboards on the browser using the Python Bokeh library.
Rating: 4.60714
Using practical real-world datasets to showcase how to visualize and analyze data with Python Pandas, scipy and numpy
Rating: 4.6
Includes visusalizations, interactions, assumptions, data issues, power analysis, outliers, and detailed interpretations
Rating: 4.6
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