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.
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).
교육 기관: Renan M d C•
The course has a very basic approach. It's much more basic than I have imagined and to be honest it is not worth paying for. Everything taught here could be learnt on youtube in 1 or 2 hours. I was expecting basic exercises using data science tools, I mean, the same approach used by academic books: first you learn some concepts and then you make some exercises, then you proceed to the next topic. I'm not saying that what was presented was not good, it was great. But it could have been much deeper.
교육 기관: Tim R•
The course was very generic and high level. I learned a few things, but the information is generally only useful to someone who is coming into the topic of Data Science with zero knowledge. Rather than having this course as part of the specialization, it would make more sense as a recommended prerequisite for those looking for a general overview of data science. Quizzes felt like busy-work, testing arbitrary facts from the reading in many cases.
교육 기관: Priya A M•
It would have been more time-effective for me to read the Wikipedia page on data science than spend the time watching these videos. The videos are much too basic with absolutely nothing technical and a fair amount of repetition of the themes across all weeks, for example, needing to be a good storyteller. The entire three module course could have easily been condensed to one module and something more substantial could have been added instead.
교육 기관: Kenneth I•
Mostly awful. The majority of the videos are just college professors talking about "curiosity, and passion for data analytics" No concrete examples, just a lot of fluff. Actual verbatim: "A data scientist does data science" The quizzes are a joke. This honestly felt like a waste of time. I'm no closer to learning the "hard skills" necessary to become a data scientist than at the beginning of the course.
교육 기관: Sima S K•
I wouldn't spend much time on this course. Although it is informative, it is filled with marketing for IBM and lengthy and sometimes repetitive interviews with people who work in this field. I'd rather skip these and jump to the real learning, software and analytics skills. Most people who are taking these courses already know this stuff and plus all this information is available for free online.
교육 기관: Konstantinos K•
Extremely basic and introductory course that does not really give very much valuable information.
Also, the peer graded assignment format is not suited (is not optimal) in my humble opinion for self-paced courses, as i do not want to have to wait for another person to review my work in order to receive the certificate... Just take a look at the discussion threads...
교육 기관: Oedhel S•
Very thorough for anyone who is interested, but doesn't know what data science is. However, it is mind-numbingly basic and most of the reading is more theoretical application than instruction. Way too long of a course for how little information there was. The quizzes were frustrating, as well, as they simple referred to the reading, but didn't reinforce concepts.
교육 기관: Justin S•
Very basic introduction. Would have liked a little more substance than just the QnA section with some people in the field and a couple short readings. This entire course could have been the first week in a real course. I also think the quizzes could have been better. They just copy paste sections of the reading to make sure you read the reading assignments.
교육 기관: George O•
[Reviewing the entire IBM Data Science specialization but points are applicable for each course]
I signed up for the IBM Data Science specialization and I was genuinely excited to start it for some 4-5 weeks (I had a GCP exam coming up). I eventually started the specialization beginning of August `20 and started making my way though it and I was amazed … amazed of how much a pile of bullshit this specialization is. I made it though the first 4 courses and at the end of the SQL for data science I couldn’t take it anymore. Here’s why:
1. First and foremost, the entire specialization (all 4 courses I have taken at least) were full of typos and broken URLs which a lot of other students confirm as well. This does not speak professionalism to me but whatever, lets move on.
2. The in-video quizzes and following tests are simply ridiculous … you are expected to have memorized content word by word rather than understand thing for your own and be able to explain them. Some of the question were so far away from tech courses it is not even funny.
3. The final assignments are a total joke. We are asked to review each other which IMHO is a terrible idea since we are all just starting up. Nothing stops you from giving top marks to a bad assignments and vice versa.
4. We eventually got to the more techy part and even got code snippets and jupyter notebooks to look through but they were still bad. There was no proper order in which information was presented i.e. you would read python and seaborn code in the SQL course’s tasks even though python and matplotlib/seaborn are discussed in the following courses.
5. And my final and biggest problem with this whole specialization is that it all feel like an extended advertisement of this piece-of-dodo tech inbred excuse-of-a-software called IBM cloud. There are constants up-sells here and there how almighty IBM is and how great their cloud and IBM Watson Studio are … they are not. I had to spend 2+ hours fixing problems with jupyter notebooks and their cloud just to complete my assignments which both took me 30ish minutes. They mention open source and even though there are open source equivalents to jupyter they insist using IBM cloud. I kept having the feeling they are more focused on promoting IBM products than actually bringing quality content.
6. Now after finishing the SQL course there was a 1min survey which I gladly filled in basically letting them know their specialization if terrible and is doing more harm than good in my opinion. I even sent them a quick challenge because I do not think IBM maintains this course at all or even reads the reviews. You can see my challenge to IBM here: https://bit.ly/3geOyfb
I was very saddened by the quality of the specialization and the content and was wondering whether I should even try and finish the remaining courses but after reading some reviews on the remaining courses I figured out it was just more of the same. If you are in the same boat I would recommend the kaggle micro-courses which I will focus on starting next week.
In conclusion, I got this whole specialization for free via financial aid and I have to say even though I did not pay a dime I feel I need to be compensated by IBM and refunded real money for torturing myself with their courses.
교육 기관: Stephen L•
I took this course and completed then got my 'digital badge'. However, for me and 100's of other students (according to the forums) our grades and progress disappeared. Coursera, are telling students to report the issue but after 2 weeks and hundreds of complaints nothing has happened.
The course itself is OK but when you are PAYING it is very poor support.
교육 기관: Shuvo S•
More like a marketing stint than an actual data science course
교육 기관: Rubin Q•
Just a lot of talk. Might as well have youtubed that question.
교육 기관: Ashmini G K•
This was a great introduction to the field of data science. Having videos interspaced with readings made it easier to maintain focus. The speakers in the videos were super engaging and I liked the upfront warning that data science involves continuous learning, and a willingness to look up stuff and practice until you understand how to do new developments in field. As a researcher who writes reports for shareholders, I felt like students could have benefited from a warning that after you figure out 5 possible solutions to a problem, and detail them in your conclusion and recommendations section, few of the stakeholders will actually read or implement the recommendations. But, hey, at least you'll have fun doing the analysis.
Although the e-note format was great in theory, I found the traditional technique of writing stuff down while watching the videos and reading the material to be more useful, as I didn't need to be logged into the site to study my notes. It's great that both options are available and learners can use the option that best fits their learning style.
교육 기관: Shelley•
The course provides a good overview of data science in general. I particularly liked the definitions of a data scientist and data science. Mr. Haider's definitions are inclusive, broad and encouraging, He says one of the most important traits for a data scientist to possess is curiosity and that tools and techniques can be learnt.
The course also touches upon hot topic areas that people have heard of but most do not understand - i.e. Machine Learning, Neural Networks, Data Mining and Big Data. I have a much better idea what these terms mean now along with the tools of the trade. The course was quite short and concise. I found it the perfect pace for me. The quizzes matched the content and there was nothing extraneous.
I am looking forward to the other courses in the specialization. A quick glance has shown me that the difficulty level increases quite a lot in the other courses and I would definitely have to invest a lot more time in them. The start has been gentle and encouraging, thank you!
교육 기관: Deleted A•
I do not having any background of Data Science but after go through this course I am having a good understanding about what is data science,what skills are needed to become data scientist etc.Additionally, clear all my confusions .Now I am aware about the correct path to learn data science,also what qualities are required to become a Data Scientist i am also aware about that.
A very good experience i had about data science after go through this course.All real life scenarios are discussed and real life experiences are shared by various data scientist.Excellent course with a very good content for beginners who do not anything about data science.
If anyone is having a little bit knowledge about data science then after going through this course you should know what are the areas in which you can improved, a correct path to build a carrier in data science.
교육 기관: Mil Á•
Very good course to understand the environment that encompasses the area of Data Science and data Analytics
Good to understand the objective of this carrier, the scope, objetives how it supporting the different verticals industries business, an the role it plays in building the strategy, also provides indication on what it takes to be a Data Science, good introduction to key related tools or solutions supporting the Analitycs evolution Artificial intelligence neural networks.
closing with key elements to be taiking into account at the moment to elaborate and provide Report & results by Data Science, never the less providing the relevance and demand that Data Science carrier in having at this moment due to the key results that provides in different scenarios of the day by day activities Industries, Science , marketing , sales etc
교육 기관: Joe I•
I really enjoyed the course. It was very informative as an introduction to Data Science. I learned many concepts that will prove useful when taking other courses in this certification program. The only thing that I would change is the definition of a Data Scientist. While it is an interesting way to define a Data Scientist, a data scientist is what a data scientist does, I think it does not give a student a reasonable idea about the professional. This definition may be valid, but, to me, indicates that the profession is not well-established yet. Also, I feel that the main goal of Data Science is to provide actionable insights to decision-makers, as opposed to solving problems. But, otherwise, this was an excellent course that I would highly recommend to others who are interested in the subject manner.
교육 기관: Elzbieta K•
This course offers a great introduction when you heard about data science, but cannot really relate to it nor give your own concise answer to what "Data Science" is or what a "Data Scientist" does. I loved the interviews with the different students at the beginning, inviting different disciplines and backgrounds to the "Data Science Table". Professor Haider and Professor White give a thorough outlook on data science and career possibilities as well as skills that are necessary to succeed. The readings cover subjects like "Data Mining" and "Data Science Project Report Writing" and give a great introduction as well as guidelines to use later on the job. Great job they have done putting this course together! And I am looking forward to the next modules of the "IBM Data Science Professional Certificate"!
교육 기관: julie c•
As a novice to Data Science this course met me where I was, at the very beginning, and provided an organized, overview of this evolving career field. The balanced mix of types of media used kept my interest and periodic comprehension checks along the way provided reinforcement of key concepts. As a visual learner I enjoyed the option to print out transcripts of all videos and reading assignments for note taking and highlighting. It was refreshing as well as encouraging to discover that 'soft skills' are highly prized in a good data science team member. I was energized to learn that I will be able to develop the skills and experience necessary to pursue a career in Data Science or Machine Learning and am eager to get started on the next course required to earn my Professional Certificate.
교육 기관: Fatima G•
Even though I can not pass the quizzes and final assignment*, I have watched the videos and read the readings and answered the questions and I found this course very very very useful, because I am new at Data Science and this course give me the overview of what is data Science really is and How can someone become a Data Scientist. I really thanks Coursers and IBM. :)
*P.S: I am in Iran. Unfortunately there is a lot of problems being an Iranian. There are sanctions and limits against Iranian "People". But it is very sad that these people were not be able to use these free educational material. I passed courses in Coursera but I Can not get certificate because the name of my country were not in the list. We are also a human being.
With respect :)
교육 기관: Jeel•
This is really a great course. Although, I am studying Data Exploration and Visualization for Data Science in school, there was a lot to gain from the course and a lot that I did not know. It really gave me a perspective of what is data science today and it surely helped me get a direction into the field and I am more confident now as to what I want to do in my start of the career as a Data Sciencist and what should I expect while preparing for the interviews and while performing responsibilities at work. And the best part was that course offers insights from some of the very big players in the industry and I think that really helps understanding Data Science from their level.
교육 기관: Caitlin L•
I must have missed it but there were more than ten components in the final deliverable as far as the reading exercise went. More specifically, the differentiation was not clear as to which of those components were the ten main components. So, extra clarification would be good. Sometimes the content seemed to contradict itself, being that there were so many lecturers, so maybe a recap as to what the definitive answer is would also be really nice too. Maybe another lecturer could be added separately at the end of each section to recap what you expect the student to understand or to summarize everyone's answer into a more definitive answer.
교육 기관: Suzanne L•
The instructors and course material do a great job in covering the field of data science and explaining why data scientists are and will continue to be of immense value in the future. As someone with an operations management background and no formal academic education in Data Science such as PhD/MS in Statistics, Mathematics, CS etc., my initial decision to learn DS was serious, yet I still had a feeling of uncertainty in making this shift. Jumping into a new field and gaining quant skills can be daunting, but this introductory course really helped me to lay a foundation and solidify my intentions in pursuing this career track.
교육 기관: Daniela R•
Hi guys, you have done a fantastic job with this course! I really enjoyed it.
I appreciate the fact that you have included diverse set of students for interviews. Going forward, it would be great if you could identify a female co-instructor to add more diversity and different perspective to the structure and presentation of the materials. I believe that having a woman as instructor (not only voice over) would make the whole topic more accessible for women participants.
Could you share some statistics on the proportion of women among students who enrolled for the course and graduated?
Thanks a lot.
교육 기관: Vineet M•
This course motivates to learn data science and know it's applications . The course is well framed which provides a crux of the data science background while giving a detailed view on the day-to-day task performed by a data scientist. This course not just only talk about the coding skills and maths but also the soft skill that data scientists require . The course talks about curiosity and storytelling as the most important soft skill for a data scientists and also tells its application while performing a task. This course is a must before diving in the deep world of coding, statistics and maths.