Interested in learning more about data science, but don’t know where to start? This 4-course Specialization from IBM will provide you with the key foundational skills any data scientist needs to prepare you for a career in data science or further advanced learning in the field. This Specialization will introduce you to what data science is and what data scientists do. You’ll discover the applicability of data science across fields, and learn how data analysis can help you make data driven decisions. You’ll find that you can kickstart your career path in the field without prior knowledge of computer science or programming languages: this Specialization will give you the foundation you need for more advanced learning to support your career goals. You’ll grasp concepts like big data, statistical analysis, and relational databases, and gain familiarity with various open source tools and data science programs used by data scientists, like Jupyter Notebooks, RStudio, GitHub, and SQL. You'll complete hands-on labs and projects to learn the methodology involved in tackling data science problems and apply your newly acquired skills and knowledge to real world data sets. In addition to earning a Specialization completion certificate from Coursera, you’ll also receive a digital badge from IBM recognizing you as a specialist in data science foundations. This Specialization can also be applied toward the IBM Data Science Professional Certificate.
This is a great course for anyone willing to start exploring the field of Data Science. It starts with basic definitions with proper examples that helps one understand this field with a greater ease!
It would be nice if you could update the material since some tools have changed either name or the way they look compared to the videos/images. Very good material though, I enjoyed the course much.
This was a critical course for me. Understanding the data scientists workflow which includes customer\client interaction has help me in understanding how to proceed in future endeavors.
Great course easy to follow, very good notes, videos and guidance on how to complete the assignments. This is a great introduction course to begin your knowledge and training to be a Data Scientist.
I learned a lot but that might not be a good indicator as I didn't know much about Data Science in the first place. It just fueled my need to know more about the subject so on my side, it's a winner.
The course is overwhelming for a beginner with no experiecne of programming. The examples given in the class seem difficult and should have been of a lower difficulty level to keep the hopes high.
It is self paced giving a good grounding on the subject provided you are an inquisitive & enthusiastic learner. It does not provide a deep dive but gives a road map for self learning.
One of the best course I completed on Coursera. All the learning material is well organised and easy to understand. Also the non-graded sections regarding relational databases are interesting.
I liked this course very much. The way it is organised to collect different data scientists opinions about the same topic, make it very valuable to the ones who are starting the road to Data Science.
Great course with practical approach to tools that come handy beside data science with python such as git and github, Some basic R coding and a great introduction to IBM Watson studio and cloud.
It is a good course, teaching about the general process and life cycle of a data science project. Excellent tips are provided. Overall, I feel it was lacking a bit in content for 3 weeks.
Covers the basics, but might be a little difficult for a complete beginner. Manageable, but difficult. Needs more help using SQL within a Jupyter Notebook which should be in the earlier labs.
Showing: 20 of 10,000
Very basic course, to be honest. The grading seemed to be dependent on memorizing exact quotes from videos. Looking forward to some of the more advanced courses in this series.
Too much introduction. There is no need to spend so much time on it. People that take this course usually understand what is data science. they need to learn real knowledge, not spend the whole week on introduction.
Videos often have disjointed or unrelated elements. Final week quizzes and mid-video questions often have useless or otherwise unhelpful reading questions. An example from week three's final quiz, "True or False: The Untied States Economic Forecast is a publication by McKinsey University Press." The answer is false and is covered in the reading, but the question has absolutely nothing to do with data science.
Too basic.
If you live under a rock and have never heard of Data Science, a Data Scientist or any terms related to this industry then this is a wonderful course for you.
For everyone else, it is a total waste of time.
This was a good introductory course, especially as someone with basically zero experience in the field. I've been struggling with where to begin (should I take a course on Python? R? What languages are even useful? WTF is cloud computing?) And this course gave me a good starting off point. That said, it wasn't technical AT ALL. It's really just a bunch of "fireside chats" with data scientists, talking about the languages they use, what concepts they're used for, what knowledge is necessary and what isn't, etc. If you're looking for a "roadmap" to continue learning on Coursera, this is it.
This is exactly what I feel the college experience gives students that online or self-taught learning lacks: context. AKA there are a billion courses on Python on Coursera, but none explain WHY I'm learning Python. This course does that. I'd recommend this course for anyone looking to start with data science from zero.
Excellent quality content! It's a great introductory course that really gets you interested in Data Science. I would highly recommend it to anyone curious in learning about what Data Science is about.
Very learning experience, I am a beginner in DS, but the instructors in this course simplified the contents that made me I could easily understand, tools and materials were very helpful to start with.
Very, very basic... completely useless and a waste of time. I feel like the only purpose of this course is to drag out the certification process so that it costs you more money...
I thought this course introduced the topic of data science very well. I think I have a much better idea how to describe data science and common terms associated with the field (like machine learning).
This course is not consistent with someone who would sign up for an entire certificate. This course is more suitable as a recruitment tool for a certificate program. Watching these videos was an absolute waste of my time.
Should this even be a course? Like they just say things that anyone can find the first thing on google if search you data science.
Very learning experience, I am a beginner in DS, but the instructors in this course simplified the contents that made me I could easily understand, tools and materials were very helpful to start with.
Poor course overall, not much "meat". An introduction to the subject that could have been given in one hour of lessons.
I throughly enjoyed the course and the fact that everything was explained thoroughly. I always enjoyed Dr. White's personal experience with Data Science as well as other Data Scientists point of view.
The course seems poorly pieced together with videos from Big Data University - which is now known as Cognitive Class. There is mainly little coherence into what the course is trying to teach in all the videos. Readings were given on a rather low resolution image file - that makes it difficult to read and kinda 1990s feel. Is it that difficult to save the pdf in text or include a higher res image file?
Similar to the point that a data science report should indicate the details and affiliations of the person writing the report, many speakers in the videos apart from the two professors does not have any background information. Who are they? Where are they from? What background are they speaking from? All these are important context for learning.
I did learn something from the final assignment though. However, that was personal reflection and learning from peers. Thinking whether I should continue with this course.
Waste of time. Most of the material was "fluff" about data science. What was actually useful could have been accomplished with a 2-3 page pdf. Only finished it, because I'm taking it as part of the IBM specialization through my work. I REALLY hope the other courses are more useful and worth the time. Very disappointed in this course.
useless, wasting time
very useful. i liked and enjoyed the journey of learning in these five weeks. the instructor is very clear and taught very interestingly. Thanks to her. she looked poised and cheerful and professional
Terrific introduction to the Data Science course. Never expected but was extremely excited with the quality of content, speakers and a very honest attempt to making this course interesting.
Krishna
The course doesn't teaches anything except for explaining data science benefits and examples.