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IBM Data Science

$35.00

(6 customer reviews)
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Prices differ based on Coursera’s programmes. 

Coursera might get your enrollment for free, you only pay for the certificate

Data Science has been ranked as one of the hottest professions and the demand for data practitioners is booming. This Professional Certificate from IBM is intended for anyone interested in developing skills and experience to pursue a career in Data Science or Machine Learning.

This program consists of 9 courses providing you with latest job-ready skills and techniques covering a wide array of data science topics including: open source tools and libraries, methodologies, Python, databases, SQL, data visualization, data analysis, and machine learning. You will practice hands-on in the IBM Cloud using real data science tools and real-world data sets.

It is a myth that to become a data scientist you need a Ph.D. This Professional Certificate is suitable for anyone who has some computer skills and a passion for self-learning. No prior computer science or programming knowledge is necessary. We start small, re-enforce applied learning, and build up to more complex topics.

Upon successfully completing these courses you will have done several hands-on assignments and built a portfolio of data science projects to provide you with the confidence to plunge into an exciting profession in Data Science. In addition to earning a Professional Certificate from Coursera, you will also receive a digital Badge from IBM recognizing your proficiency in Data Science.

LIMITED TIME OFFER: Subscription is only $39 USD per month for access to graded materials and a certificate.

6 reviews for IBM Data Science

  1. lauren j

    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.

  2. julian l g

    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…

  3. parker d

    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).

  4. chin-hung y

    Good for fundamental knowledge of data science and data scientists.

    It is also inspiring for young people like me to get ready to step into the world of data science.

    Great course

  5. rick n

    I did not learn much from this course. I did not enjoy seeing the young data scientists talking about their jobs. I was not too impressed by Dr. Haider or the professor from NYU.

    Dr. Haider misused some words, such as “judgmental” and “argumentative”. Without any evidence or examples for support, he claimed that it was more important for a job applicant to have a sense of humor than technical skills.

    This course should have named specific techniques used in data science, and how to acquire the knowledge. Regression was mentioned, but the explanation was inadequate. Perhaps the explanation should have been omitted. K-nearest neighbor was mentioned.

    Many students want to know what courses to take next, what computer languages to study, etc. What are the computer programming languages of the future?

    Students cannot learn everything. Would it make sense for someone to skip some things, and to focus on others? Should everyone learn Python? Does everyone need to learn SQL? What about Tableau? Is that worthless?

    How should students set their learning priorities in order to achieve a basic or minimal skill set within 3 or 6 or 12 months?

    Remember that most Coursera students already have a college degree.

    The course was created several years ago, so I think it needs to be updated regarding developments of the last three years.

  6. souro

    It was a good introduction for everyone even novice.

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