“Colors for Data Science A-Z: Data Visualization Color Theory” Colors for Data Science A-Z: Data Visualization Color Theory is a course that explores color theory and fundamental color concepts to assist in creating effective data visualizations in data science. The course is beneficial for data scientists as it focuses on the presentation of findings to management, clients, or large audiences. Currently, udemy is offering the Colors for Data Science A-Z: Data Visualization Color Theory course for up to 89 % off i.e. INR 389 (INR 3,499).
Who can opt for this course?
- Anyone looking to develop their data science presentation abilities
Course Highlights
| Key Highlights | Details |
|---|---|
| Registration Link | Apply Now! |
| Price | INR 389 ( |
| Duration | 03 Hours |
| Rating | 4.4/5 |
| Student Enrollment | 6,578 students |
| Instructor | Kirill Eremenko https://www.linkedin.com/in/kirilleremenko |
| Topics Covered | N.A |
| Course Level | N.A |
| Total Student Reviews | 1,095 |
Learning Outcomes
- Make eye-catching palettes with colour schemes
- Any data visualization’s color aesthetic should be evaluated
- Understand the distinction between CMYK and RGB
- Make Data Science visuals that have an effect
- Recognize how color schemes function
- Understand what a tone, shade, and tint mean
- Understanding what an achromatic colour is Utilize programs like Paletton, ColorBrewer, and Adobe Color
Course Content
| S.No. | Module (Duration) | Topics |
|---|---|---|
| 1. | Introduction (02 minutes) | Welcome to the course |
| 2. | Color Theory (38 minutes) | Color Theory Map |
| What is a color? | ||
| The Color Wheel | ||
| Tints, Shades, and Saturation | ||
| Achromatic Colours | ||
| CMYK vs RGB | ||
| Color Blindness | ||
| Color Theory | ||
| 3. | Colours & Emotions (26 minutes) | Why this section is important |
| Meanings of Colours | ||
| Warm and Cool Colours | ||
| Yellow Orange Red | ||
| Blue Green Purple | ||
| Colors and Emotions | ||
| 4. | The Tools (24 minutes) | Hello! This is what you will learn in this section |
| Adobe Color | ||
| Paletton | ||
| Color Brewer 2.0 | ||
| 5. | Colour Schemes (44 minutes) | Color Context |
| Color Schemes | ||
| Monochromatic Colour Schemes – REAL Data Examples | ||
| Analogous Colours – REAL Data Examples | ||
| Complementary & Split-Complementary Colours – REAL Data Examples | ||
| Triadic & Tetriadic Colours – REAL Data Examples | ||
| Color of the background | ||
| Color Schemes | ||
| 6. | Data Science Project Walkthrough (01 hour 30 minutes) | Project Brief: Vitamin Trials |
| Download & install Tableau Public | ||
| Building the visualization | ||
| Testing out color palettes | ||
| Applying the split complementary color scheme | ||
| Coloring the subcategories | ||
| Applying the triad color scheme | ||
| Applying the analogous color scheme | ||
| Section recap | ||
| 7. | Bonus Section (51 seconds) | Your Super-Special Invitation |
Resources Required
- A desire to succeed and a working knowledge of computers
Featured Review
JOAN GENIS VALVERDE ALBONS (3/5): I loved the first 5 sections, but was completely disappointed by the 6th one. I think it serves more as an advertisement for the Tableau course than for a learning purpose. I would prefer a less powerful but free solution (OpenSource) no quiz nor real exercices in it. A pity. In addition I experienced some issues with the .csv (it was not correctly connected to Tableau and I had to convert it to Microsoft).
Pros
- Guillermina Montanari (5/5): This is a great course with the basics of how to think about colors in a presentation.
- carlos barboza (5/5): His example on the scatter plot using Tableau was OUTSTANDING! Voila!
- Dunja G (5/5): It gave me good perspective how to connect a color with data in data storytelling.
- Erich Brockmann (5/5): Loved the course, good info, like the presenters’ interactions as well.
Cons
- Niels van der Windt (2/5): Course presentation style is what made me give a bad review.
- Niels van der Windt (2/5): It also seemed as if the (very irritating) music in the beginning and end of each lesson was used to artificially raise course duration.
- Ryan (1/5): The presentation was so bad that I couldn’t make it through 3 lectures without getting annoyed.
- A Williams (2/5): The written English is awful – how hard would it be to get a native English speaker to check the course over before publishing it?
About the Author
The instructor of this course is Kirill Eremenko who is a Data Scientist with 4.5 Instructor Rating and 604,562 Reviews on Udemy. He/she offers 59 Courses and has taught 2,279,051 Students so far.
- Professionally, Kirill Eremenko is a data science consultant with experience in the retail, transportation, retail, and financial sectors
- At Deloitte Australia, Kirill Eremenko received training from the top analytics mentors, and since he started teaching on Udemy, he has shared his experience with thousands of aspiring data scientists
- You will quickly see from my courses how Kirill Eremenko gives skilled step-by-step tutoring in the field of data science by fusing my real-world expertise and academic background in physics and mathematics
- His emphasis on intuitive explanations is one of my teaching strengths, so you can be confident that you will fully comprehend even the most challenging subjects
- To sum up, he is entirely and completely excited about data science, and he can’t wait to share my expertise and enthusiasm with you!
Comparison Table
| Parameters | Colors for Data Science A-Z: Data Visualization Color Theory | Tableau 2022 Advanced: Master Tableau in Data Science | R Programming: Advanced Analytics In R For Data Science |
|---|---|---|---|
| Offers | INR 455 ( | INR 455 ( | INR 455 ( |
| Duration | 4 hours | 10 hours | 6 hours |
| Rating | 4.4 /5 | 4.7 /5 | 4.6 /5 |
| Student Enrollments | 6,578 | 92,718 | 58,099 |
| Instructors | Kirill Eremenko | Kirill Eremenko | Kirill Eremenko |
| Register Here | Apply Now! | Apply Now! | Apply Now! |
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