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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
This course takes four weeks, 4-6h per week...

Jan 07, 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!

Sep 10, 2017

A perfect course to pace off with exploration towards sensor-data analytics using Apache Spark and python libraries.\n\nKudos man.

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von Ted H

•Jul 15, 2019

A really good introduction to Apache Spark. The course has been changed around a lot to conform with the latest syntax and to make it easier to get to work with data. Many of the videos still refer to the old syntax but the examples have all been brought up to date. Students no longer need to generate their own data (with node-Red) but can immediately get to work on pre-generated data. All this change has made some parts of the course a little confusing, but a little perseverance will overcome these problems.

von Daniel T

•Apr 21, 2019

Be careful when signing up for your IBM Cloud Instance and remember to shut it down when you're not using it. I ran out of free hours and unfortunately they're no longer free after the first 30 days which either makes it impossible or expensive to finish this course. Also, 30 days might mean an arbitrary 30 day billing cycle, perhaps starting on the 1st of the month.

von Alev K

•Sep 26, 2018

It was fun learning to me in Spark Python. Python is more attractive now, see it is not that complicated visualisation and calculation functions in it. I could manage SQL very well which helped me a lot. now i feel more confidant in Python.I use to like more R before now i see python advantages regarding R in terms of performance and cost effects.

von Shakti s

•Dec 28, 2018

I would like to Recommend this course because this course Not only taught you the well developed Syllabus but also test your ability /skills to tackle problems in submitting Assignments and which i think is the exciting part and challenging.

that moment when your are dealing with the problem and finally solved that, that work really paid off.

von daniel b

•Dec 17, 2019

This class make me confident in using apache spark for data projects that I may need. I really enjoyed how simple and effective it was. Very practical, easy to follow, high level course. Can not wait until the next course. You should probably have some experience with data frames and lambda expressions before coming into this class.

von Michael B

•Jul 23, 2019

Extremely well done course!!!

I am not sure what the comments about bugs in the course are about; I did not experience any.

I've taken about a dozen or so courses on Coursera, and this was one of my favorites. Everything is well explained and well laid out.

I'm excited to take the remaining courses in the series :D

von Gusti R A

•Feb 17, 2019

This course is very recommended if you want to bring your Data Science skill to the next level. The instruction is very clear and easy to understand. The assignment is really challenging for me as the new comer in this Data Science world, but yeah, i finally can finished this course. You should take this course.

von hamza j

•May 01, 2019

Best course for People who have basic understanding about Python programming, Machine learning and statistics. The assignments are flexible and easy to complete. The course includes both theoratical and technical aspects of data science

von ASHISH J

•Apr 15, 2019

awesome course, got a good understanding of statistics in an intuitive manner.

The main strength of this course is that, this course will help you to develop intuition of the whole data science concepts into the real world scenario.

von Savan R

•May 23, 2019

Covers exactly what is required for data science using spark in case IoT data applications and the fundamentals required for the advanced data science topics . I am happy with the course and the topics that I have learned so far!

von Xilong W

•Apr 11, 2017

Very useful courses to take if you are beginner of data science. The course was not detailed enough sometime. But you will surely get a global view of IOT data analysis after this courses.

von Adamya

•Jan 07, 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!

von Octavio A T N

•Oct 26, 2019

This is a very good Data Science course. It helped me a lot to think in realistic application of Data Analysis. Impressive !!!

von Tee H L

•Dec 16, 2019

I really like this learning method from IBM especially the instant quiz just to make sure I understand the important points.

von Edoardo B

•Jun 29, 2018

A wonderful course enjoyable and useful for my professional objective. Very thanks to the teacher

von Dhinson G D

•Oct 01, 2019

I love the course content. Simple but very informative and provides good practical exercises.

von Sven

•Oct 05, 2018

Very good data science specialization covering many interesting advanced technologies!

von Roozbeh G

•Jun 20, 2019

Well-taught course in an extremely important and sought-after data science field.

von Azeezur R

•Oct 17, 2018

Excellent Course with very interesting assignment and informative video course

von Jamiil T A

•Apr 26, 2019

Excellent. I highly recommend it, jump in and enjoy learning the foundations.

von praveen k

•Nov 12, 2019

First time I got the change to work on cloud data (big data). Thanks to IBM

von Khawar A A

•Jan 27, 2019

Great .. !! Big fan of sir Romeo. Great learning and awesome instructor.

von abderrahim b

•Jan 10, 2019

Excellent course! Thanks for giving of your time to share the knowledge!

von Vishal S

•Sep 24, 2018

This was really awesome. I eventually got better at this. Good course.

von Pawel P

•Apr 23, 2019

Too easy to be called advanced. I look forward to seeing what's next.