Prepare for a career in the high-growth field of data science. In this program, you’ll develop the skills, tools, and portfolio to have a competitive edge in the job market as an entry-level data scientist in as little as 4 months. No prior knowledge of computer science or programming languages is required. Data science involves gathering, cleaning, organizing, and analyzing data with the goal of extracting helpful insights and predicting expected outcomes. The demand for skilled data scientists who can use data to tell compelling stories to inform business decisions has never been greater. You’ll learn in-demand skills used by professional data scientists including databases, data visualization, statistical analysis, predictive modeling, machine learning algorithms, and data mining. You’ll also work with the latest languages, tools,and libraries including Python, SQL, Jupyter notebooks, Github, Rstudio, Pandas, Numpy, ScikitLearn, Matplotlib, and more. Upon completing the full program, you will have built a portfolio of data science projects to provide you with the confidence to excel in your interviews. You will also receive access to join IBM’s Talent Network where you’ll see job opportunities as soon as they are posted, recommendations matched to your skills and interests, and tips and tricks to help you stand apart from the crowd. This program is ACE® and FIBAA recommended —when you complete, you can earn up to 12 college credits and 6 ECTS credits.
AB
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!
RG
It's a good introductory course to know all the open-source tools available for data science. However, it will not teach you how to code for these tools apart from introducing a few basic lines.
HH
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.
TM
it becomes easier wand clearer when one gets to complete the assignments as to how to utilize what has been learned. Practical work is a great way to learn, which was a fundamental part of the course.
TM
The assignment is quite easy, you just need to understand the code and rewrite the code to finish the final assignmentThis is a very useful course to help us imagin basically what a DS do
DE
Course is god enough. However the last assessment is not. Misprints and not clear questions lead to disappointing marks in the end. Also other students marked assessments based on their understanding.
MW
Good Course. Very good overview of Python libs -Pandas, Numpy, Matplotlib, Scipy, Scikitlearn and Seaborn. I really enjoyed learning about them and seeing the usage. Highly recommended course.
AA
This course was really interesting and it was great learning experience.A big thanks to a instructor.I got to know new things like folium library (most interesting library of python according to me)
RC
The course was highly informative and very well presented. It was very easier to follow. Many complicated concepts were clearly explained. It improved my confidence with respect to programming skills.
RS
Very in-depth and rewarding project - would be a little better if more specific guidance on what to exactly include in the notebook would be better. But overall very stimulating. Thanks!
SE
Its really helpful for beginners to apply AI tools
KH
I like how things were laid out in clear and concise terms and descriptions. This is one of the more thorough interview preparation guides I've read/looked at .
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.
useless, wasting time
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.
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.