7 sept. 2017
It was really insightful, coming from knowing almost nothing about statistics or experimental design, it was easy to understand while not feeling shallow. Just the right amount of information density.
14 avr. 2020
As a business student from Bangladesh who is aspiring to be a data analyst in near future, I love this course very much. The quizzes and assessments were the places to check how much I exactly learnt.
par MITTAPELLI R K•
4 août 2020
I would like to appreciate the efforts of course instructors to start a new way of learning for us and also for giving a complete course on the basics and fundamentals of the software. I strongly recommend everyone to use this course as a foundation to learn software like git bash and R studio.
par Felix N•
8 nov. 2018
Very good overview of the basic concepts and tools required to delve into the world of Data Science. Explanations are easy to understand, lectures are easy to follow. There is far more detail and information involved regarding Git and R in general but are not necessary to complete this course.
par SARI R•
22 oct. 2018
A very useful course with a lot to learn about the basics of programming and data analysis. I have learned a lot of things and also this course has enhanced my confidence level to a higher level. Thank you coursera and John Hopkins University for providing such a wonderful opportunity to all.
par Julian K S•
18 déc. 2020
The course provides good instructions for installing R, RStudio, Git, and getting set up on GitHub. The course project offered a good opportunity to get a bit hands on with the software, but be prepared and willing to utilize outside resources (including suggested links provided in lessons).
par Karen L•
8 nov. 2018
This was my first experience taking a coursera course. I was impressed with the thorough and well thought out content. The course material was easy to follow and it was easy to stay on track. This was one of the best virtual classes I have attended. I am looking forward to the other courses!
par Brandan W•
31 déc. 2020
This is a very good introductory course to R, Rstudio, Git & Github, and lays down some a great little survey of foundational statistical analysis theory. I learned a great deal in this course. I would highly recommend it as a first step for anyone interested in learning about data science.
par Esteban A F•
6 juin 2020
Un curso muy bueno para aquellas personas que no hayan trabajado antes con R o con RStudio. Abarca temas basicos pero fundamentales para empezar a trabajar con R y GitHub. Las lecturas no son muy extensas y estan bien explicadas, lo que facilita la comprension por parte de los estudiantes.
par Rolin M•
4 août 2017
Thorough course introducing all practices related do data science.
A bit overwhelming but I mostly saw it as a lexicon of some kind; a resource to use again and again during the certification.
Hates off to the speakers who made a great job in terms of pedagogy in all video.
Max, form France.
par Rohit P•
28 janv. 2020
A very balanced and quick course to introduced R, R-studio, Github and other tools for data analysis. Also, the examples and methods of communicating critical terms are impressive and are forever etched in my memory. As a trainer myself, I will do my best to employ these in my workshops.
par Cesar P•
3 août 2020
I wish there was assistance from the instruction in case we come into problems. I did find a lot of written assistance, but in case of an issue I am unable to solve then I will need an instructor available that will go over the issue with me. I do not know if that is already available.
par David B•
25 juil. 2018
Good foundation concepts for what will be required in DS according to the instructors. Good start point and presents basic challenges to getting you set up for the rest of the certification. Other courses will be required for more breadth and depth of concepts. Very good introduction.
par Furkan K•
28 déc. 2021
Such an easy start to get your Data Analyst journey. The course is very simple and really make you feel like you're learning the core basis of Data Analysis. Highly recommend for those who are just want to start learning about Data Science or just curious about the field in general.
par Donald M•
17 sept. 2020
It is an excellent course to get started in the world of data science.
All the steps well explained without a doubt.
The course has an excellent organization.
I am totally satisfied and will continue with the courses that follow.
Thanks to the instructors for such an excellent course
par donna o•
19 mai 2020
It is a nice course which smoothly familiarize a novice data science learner to the nature and tools of their job. Although I prefer it to be taught by a real instructor instead of a robot, apart from that everything was designed carefully to introduce data science toolbox to people.
par Ricardo J d S•
17 déc. 2018
Achei de grande valia, no meu caso, especificamente, por me colocar novamente em contato com a parte mais técnica da TI - venho desempenhando papéis gerenciais a algum tempo e tinha certo receio de alterar a configuração da minha máquina para ser um "laboratório" de ciência de dados.
par Farkhadov Z•
8 août 2016
Good course for begginers like me. All information is provided very simple and it's easy to understand. Also involves srudents not only looking videos but offer books. In addition you will need to search some information yourself to complete some tasks.
Thanks for this great course.
par Veera V k•
7 déc. 2019
Even though it is a starter course to the specialization learned so many new things like amazon polly which is being used to generate these videos, R-markdown and how important is it to produce reproducible research.
A must take course for any data science aspirant
par Ting L•
24 août 2018
It's a great course for beginners. I had little knowledge about data science. I didn't even know what was R and GIt. After taking this course, I had a preliminary understanding of them. If anyone wants to learn data science without any experience, this one can be your start point!
par Tristan I•
17 janv. 2020
All the information felt applicable to my current role. The main thing I gained from this course is that I feel more confident in the tools at my disposal as a data analyst. Additionally I learned about tools I had never heard of & how to utilize them, and for that I'm thankful!
par Oskar D H•
17 mai 2021
Para conocer por primera vez Git y R, así como RStudio; y las implicaciones entorno a resolver un problema relacionado a la ciencia de datos, es un curso que lo hace de forma clara al explicar conceptos importantes para comprender el análisis de datos y hacerlo de forma optima.
par David L M•
16 août 2020
Good starting point for starting to learn data science. Short, practical course on definitions and tools for data science. I knew a little bit about R and RStudio (but not much) and didn't know anything about Git and Git Hub, and this helped me a lot to know these tools better.
par Dominic C•
25 avr. 2016
Great way to learn R and become familiar with how to use it. As a developer with an understanding of Python, Java, C and C++ I could quickly see how to use R, how to extend it and start working with it today. Very good use of supporting tools like Swirl to assist with teaching.
par Rodrigo E•
23 oct. 2020
I would prefer more courses with this format, videos and the reading section with exactly the same content, I have found that is better to read so you can go back to previous paragraphs if you didn't understand something. Both things are pretty good videos and reading section.
par Kaushal C•
11 juin 2020
The course provides a good introduction to the necessary toolbox required. It provides introduction to the Rstudio interface and Github version control system. The course helped me gain a lot of knowledge regarding Data Scientist toolbox, especially the version control system.
par Michael S•
19 févr. 2018
I found this course to be effective at getting the student to recognize the baseline set of tools, skills and behaviors expected in courses 2-10. Moreover, none of said tools, skills or behaviors fall outside the confines of typical and/or "in demand" experience. Nice work!