Introduction to Data and Data Science

with Martin Ganchev and Iliya Valchanov

4.8/5
(5724)

Introducing you to the field of data science and building your understanding of the key data science terms and processes.

22 lessons 2h
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Course Overview

Working with data is an essential part of maintaining a healthy business. This course will introduce you to the field of data science, help you understand the various processes and distinguish between terms such as: ‘traditional data,’ ‘big data,’ ‘business intelligence,’ ‘business analytics,’ ‘data analytics,’ ‘data science,’ and ‘machine learning.’

22 High Quality Lessons
17 Practical Tasks
2 Hours of Video
Certificate of Achievement

Skills you will gain

Career developmentdata analysisProgrammingTheory

What You'll Learn

You are interested in starting a career in data science? Begin with the very basics by receiving the proper introduction to the world of data with this course!

Distinguish between various data science related fields
Understand the terms traditional and big data
Integrate common data science techniques
Use specific data science tools
What are the most common data science programming languages
Become familiar with data science job positions and alternatives

Curriculum

Student feedback

4.8/5

5724 ratings
5 stars
4835 (84%)
4 stars
758 (13%)
3 stars
107 (2%)
2 stars
15 (0%)
1 star
9 (0%)
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12.07.2022
Much of the information seemed overwhelming and not important at the same time. Personally, I felt the semantics of the definitions (data scientist vs data analyst) to be very boring and not particularly useful, and therefore could not remember the difference between the terms. The structure I like. The videos and explanations were clear. I enjoyed the course more when it went more into the graphs and process of machine learning. The questions just had to do mainly with memorization. The brief videos were not enough to engrain the terms and subtle differences into my memory. I failed almost all the quizzes the first time and had to retake them to get a passing grade. Maybe an aniki flashcard setup to prep for the quizzes would be a solution to get the buzzwords to stick in memory. I think I'll like the rest of the course better when the topics are more interesting and get more into specifics.
02.11.2022
I really like the course, but maybe it is just the choppy audio (the voice is fine just the sudden start and start) or maybe it is just me and I am not in learning mood as (I am kinda tired) I am a little bored. Though, this is the introductory course so it isn’t to the interactive part of it yet, so that might be a thing which is fine. Without a foundation, how can you build a multistory house? I say 4 stars for several reasons. Not because of the course, though. Here is one example: Some people will not look at 5 stars and because of possible bias (and kinda the same with 1 stars) they will look at 2-4 star reviews first. (I am not saying this is a majority, just some). The course’s info-graph itself is going to be extremely helpful for remembering the terms, that doesn’t include the breakdown of the info graph and other information in the course.
07.11.2022
In some questions the context was not immediately obvious to me - are talking about this info-graphic or the previous one? why is sales forecasting not ML? etc.. I have a feeling, that I would need more quiz questions to really solidify the new knowledge - for example I can repeat the examples about qualitative and quantitative analysis from part one, but I'm not really sure I got the principle right. It's really good that the course points out several times, that in many places these terms are being used differently - they really were in my previous company and it pops out in random places... I'm happy to be show other perspective.
09.11.2022
Good course for understanding data analysis 👍
04.11.2022
+: the content is well structured. - : the explanation is based on the flow of the data. the table brings several dimensions to this flow. all dimensions are not as important. it would be clearer with a graph with data associated to it than with a table: there is a lot of type of relations that are not very specific and fit in a table, and that are a lot clearer with another presentation. maybe it's a question of taste.
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“The first step is the most important. Intro to Data and Data Science focuses on the field of data and data science as a whole. I will guide you through the terms, disciplines, and tools involved, and discuss the possible career paths in front of you.”

Martin Ganchev
Worked at the European Commission
Introduction to Data and Data Science

with Martin Ganchev and Iliya Valchanov

Start Course