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Opiniones y comentarios de aprendices correspondientes a Fundamentals of Scalable Data Science por parte de IBM

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Apache Spark is the de-facto standard for large scale data processing. This is the first course of a series of courses towards the IBM Advanced Data Science Specialization. We strongly believe that is is crucial for success to start learning a scalable data science platform since memory and CPU constraints are to most limiting factors when it comes to building advanced machine learning models. In this course we teach you the fundamentals of Apache Spark using python and pyspark. We'll introduce Apache Spark in the first two weeks and learn how to apply it to compute basic exploratory and data pre-processing tasks in the last two weeks. Through this exercise you'll also be introduced to the most fundamental statistical measures and data visualization technologies. This gives you enough knowledge to take over the role of a data engineer in any modern environment. But it gives you also the basis for advancing your career towards data science. Please have a look at the full specialization curriculum: https://www.coursera.org/specializations/advanced-data-science-ibm If you choose to take this course and earn the Coursera course certificate, you will also earn an IBM digital badge. To find out more about IBM digital badges follow the link ibm.biz/badging. After completing this course, you will be able to: • Describe how basic statistical measures, are used to reveal patterns within the data • Recognize data characteristics, patterns, trends, deviations or inconsistencies, and potential outliers. • Identify useful techniques for working with big data such as dimension reduction and feature selection methods • Use advanced tools and charting libraries to: o improve efficiency of analysis of big-data with partitioning and parallel analysis o Visualize the data in an number of 2D and 3D formats (Box Plot, Run Chart, Scatter Plot, Pareto Chart, and Multidimensional Scaling) For successful completion of the course, the following prerequisites are recommended: • Basic programming skills in python • Basic math • Basic SQL (you can get it easily from https://www.coursera.org/learn/sql-data-science if needed) In order to complete this course, the following technologies will be used: (These technologies are introduced in the course as necessary so no previous knowledge is required.) • Jupyter notebooks (brought to you by IBM Watson Studio for free) • ApacheSpark (brought to you by IBM Watson Studio for free) • Python We've been reported that some of the material in this course is too advanced. So in case you feel the same, please have a look at the following materials first before starting this course, we've been reported that this really helps. Of course, you can give this course a try first and then in case you need, take the following courses / materials. It's free... https://cognitiveclass.ai/learn/spark https://dataplatform.cloud.ibm.com/analytics/notebooks/v2/f8982db1-5e55-46d6-a272-fd11b670be38/view?access_token=533a1925cd1c4c362aabe7b3336b3eae2a99e0dc923ec0775d891c31c5bbbc68 This course takes four weeks, 4-6h per week...

Principales reseñas

AA
6 de ene. de 2020

A very nice introduction to Apache Spark and it's environment. As a bonus, it's also a very nice refresher to your basic statistics!!! Great course!

GA
5 de may. de 2020

Its a great experience especially with this course. I appreciate Romeo the way he designed the assignments. It brings out the clear understanding.

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351 - 363 de 363 revisiones para Fundamentals of Scalable Data Science

por Smriti C

8 de jun. de 2020

Not a recommended course

por Felipe M M

18 de sep. de 2019

Videos are old. It feels like he had a bunch of material and put them together to create this course. For example: There are assignments that they give you the answer because the questions are not supposed to be there. He doesnt teach, instead, he reads a script. The assignments are not challenging and you dont feel like you learned. Horrible and painful.

por Gerardo M

10 de jun. de 2020

A lot of the code explained in the video doesn't work with Python 3. The course is missing real examples with updated code working with the latest versions. If I have to go on the internet to learn how to pass each programming assignment of this course because the videos are outdated then I can do this for free, no need to pay the 40 euros/month. Thanks

por Sanggyu B

13 de sep. de 2020

This is by far the worst.

The content is very poor so that 'advanced' should be removed.

In addition, the lecturer's English is unclear and not easy to understand, however, as there is empty content you don't need to worry.

I just wasted my money and time.

por Deleted A

12 de nov. de 2020

Course materials is not up to the with the latest state of the IBM Cloud environment. IBM Cloud environment is super buggy. Need to transform this training to make the user use its own environment and not push the IBM Cloud infrastructure.

por Vladyslav

5 de jul. de 2020

не можу зареєструватись за посиланням https://dataplatform.cloud.ibm.com/, будь ласка, перевіряйте справність всіх ресурсів перед тим, як публікувати курс. дойшов до практичного заняття і не зміг зареєструватись.

por ashwani b

4 de abr. de 2020

Structure and flow is the reason people pursue online courses then studying from any random youtube video tutorials. This course lacks those basic properties. Major concern was to promote IBM cloud than to teach.

por Ahmet Y

17 de mar. de 2020

After the IBM Data Science Proffesional Specialization this course was very inadequate. Lambda calculus is not explained well.

por Mike H

1 de ene. de 2020

Not well structured in my opinion. Difficulty of content not well balanced. Outdated presentations and content...

por Goce Z

19 de may. de 2020

easier to just make it labs and some reading as all the videos are just watching the instructor type code

por Kaustav S

14 de may. de 2020

Not a course relevant to data science, what needed in the market perspective

por Weiquan L

20 de sep. de 2020

course material is inconsistent and not well prepared.

por Булаев С А

26 de ago. de 2020

To easy to be advanced ML course.