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Data Science Methodology

Introduction to Data Science,

Despite the recent increase in computing power and access to data over the last couple of decades, our ability to use the data within the decision making process is either lost or not maximized at all too often, we don't have a solid understanding of the questions being asked and how to apply the data correctly to the problem at hand. This course has one purpose, and that is to share a methodology that can be used within data science, to ensure that the data used in problem solving is relevant and properly manipulated to address the question at hand. Accordingly, in this course, you will learn: - The major steps involved in tackling a data science problem. - The major steps involved in practicing data science, from forming a concrete business or research problem, to collecting and analyzing data, to building a model, and understanding the feedback after model deployment. - How data scientists think! LIMITED TIME OFFER: Subscription is only $39 USD per month for access to graded materials and a certificate.

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Rating 4.3 based on 1,643 ratings
Length 4 weeks
Effort 3 weeks of study, 2 - 3 hours/week
Starts Jun 28 (13 weeks ago)
Cost $38
From IBM via Coursera
Instructors Alex Aklson, Polong Lin
Download Videos On all desktop and mobile devices
Language English
Subjects Data Science
Tags Data Science Data Analysis

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What people are saying

final assignment

Also, I found that the final assignment has a mistake, making the total available scores changed from 10 to 9, which force us to make a "perfect answer" to get almost a full mark (the passing mark is 8 marks).

It looses 1 star because of the final assignment, which is very vague and open to all kind of interpretations.

I am still unsure if what i wrote in the final assignment was even 100% correct (even though i got the top score), simply because these assignments are being judged by peers, not mentors.

Instructions were vague for the final assignment.

The course is good but the way the example is explained is a bit confusing, especially the when jumping from study content/material to the example.The peer to peer review for the final assignment is veeeerrryyy subjective.

Everything from how disconnected the quiz questions are compared to available information provided in the course to the peer-graded final assignment show little or now effort was put into composing this course.

Some questions are redundant such as the name of the person who designed the data science methodology or questions specific to the case study and does not necessarily provide insight into general concepts.3) Simply reading what is in the slides is not a good use of videos and cannot keep the focus of the students for a long time.4) This course might be located after the Python for Data Science course or even later so that the students could have a more meaningful final assignment, actually applying what they learned on a small data set.5) Knowing a subject and teaching a subject are two different things.

Excellent description of the processs The Final Assignment was not so easy to understand how to do it.

the final assignment is too open-ended.

Very boring The final assignment had me ham strung.

The there are specific methods shown but what if they don't fit your final assignment example?

it' s a good course One peer gave me fewer points in my final assignment.

Less than a minute after summiting my Final assignment it came back with peer review that was disappointing.

provide details on each step of Data Science methodology.enjoyed the final assignment because of all relevant topics.

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about data science methodology

Solid introductory information about Data Science methodology with challenging quiz questions.

Effective class to get to know about data science methodology.

i have learnt and things to handle the problem and process of reaching to the solution muchas gracias, excelente curso y grandes ejercicios en os LABs Complete course about data science methodology, with real-life case study I really loved the parallel case studies this course uses to help with understanding iterative data science.Thanks..!

Good Beginner Level Course The best course to get an understanding about Data Science methodology Excellent approach Great Learning in understanding the step by step process from business understanding, analytics approach to modelling, evaluation, deployment, feedback.

Excellent content and explained with details Nice course with basis understanding about data science methodology I had a few issues with the IBM cloud that could not be addressed quickly.

Excellent curse and provides a broaden knowledge about data science methodology.

Course is very helpful to understands the how to go with analytic approach through methodology.It good start for the any data science and AI aspirant Good Good Understand more about Data Science Methodology Good Narrations it is good to get experience I am thankful to my all teacher from course for providing us with best knowledge.

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very well explained

Very well explained all methodologys Quality short course and introduction to methodology Enjoyed this course.

Without this course, the training in data science is incomplete Very well explained !!!

Very well explained the concepts with examples.

Extraodinary the course Very well explained and hands on experience, Actually challenges you and make you think about the problem you are trying to solve amazing course and stuff Great course with solid pedagogy.

Very well explained I learn about how interesting it is the data science methodology The best part about this course is that you learn using Jupyter Notebook.

Very well explained.

Very well explained, easy to digest and really paints the picture of a data scientist various activities and contributions within a project.

Also the main case study was a little out of date and not very well explained.

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step by step

Very helpful and comprehensive More over theoretical course.. AS Very useful and interesting, I like the Labs and the Case studies, they help you to understand how the methodology is performed step by step.

It is really a very nice content which gives you an in depth insight on how to proceed step by step.

Gives good understanding of step by step processes in Data science.

Step by step approach, easy to understand and apply Great Course it was useful good basic course Great course, but it goes over some key concepts very quickly.

It gives you step by step approach to the Data Science.

This step by step guide is recommended.

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highly recommend

Highly recommend this course.

I highly recommend it to anyone willing to be patient to understand the under-workings of data science.

I highly recommend it to anyone who wants to learn the data science methodology in short time I loved this class!

Highly recommended.

This is a highly recommended courses to start building Data Science projects through solving real-world problems across industries.

Very informative and cover the whole life cycle of a data science project Challenging course Course describes various steps followed for Data science projects with quite practical reasoning, and understanding.Highly recommended for beginners.

Excellent This is a very easy to understand course, I always have trouble staying focus while studying but this course is very fast and keeps you interested in the subject, it explains the methodology very well and its easy for you to retain all the information, and its very friendly for people without english as their first language, I highly recommend it, thanks a lot!

I highly recommend this course, no previous knowledge needed.

I will highly recommend to this course to those students who always search for the answers about and how to clear your concept.

Nice course I highly recommend everyone to take this course as this course will teach you what are the steps that we need to take in order to solve business problem.

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each stage

I like how each stage of data science workflow is summarized to a wheel where each stage communicates with others in an efficient way.

The course guides students through an in depth analysis of each stage with examples and labs so they can follow along.

assignment could be more specific and practical Amazing job of explaining each stage of the methodology.

The examples used were poor and the definitions of each stage were not concrete, workable definitions but rather very abstract definitions.

The case study was very helpful and definitely contributed to clarify concepts presented in each stage.

This course really explains each stage of a data science project and also has exercises that help one better understand.

EXCELLENT useful and beneficial for beginner Data scientist I like this course very much as it was designed to evaluate our understand at each stage and also the lab is a great way to learn in practical.

It was a course with a good structured focus on each stage of the methodology process.

A step-by-step walk.through project exercise on a pre-determined topic/scenario with specific questions at each stage, would have probably been more useful.

The videos could've expanded the concepts more so that the differences between each stage of the Data Science Methodology becomes clearer.

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rather than

This must be an obsolete tool, which IBM stopped supporting at some point.I'm hoping the next course will allow me to run python on my cpu, rather than using a broken cloud tool.

Other sites have explained this much simpler and clearer than here It is refreshing to see a data science course that clearly talks about the methodology (which is fundamental to thinking about the process) rather than the technology (which, while useful, but the lure of technology is often used sloppily without real underlying thinking and reflection.).

I thought that the material was certainly important, but felt that the quizzes were more memory of the videos rather than an intuitive understanding of the material.

It is better to find some common examples to be understandable for all fields of studies rather than talking about patients and medical things.

Feels like too much concentration on the healthcare case study, rather than the concepts.

Found that I learned best by reading the video scripts rather than watching the videos.

The quizzes sometimes focus on arbitrary moments from the videos, to make sure you were paying attention, rather than asses the practical, applicable information you have retained.

Make this course more intuitive rather than being just all theory.

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machine learning

Maybe better to pass it after other courses to be familier with python, decision threes and machine learning.

Good course to know all the processes for approaching towards your machine learning model.

I think it's a little bit vain to introduce in such way for some people without much background in statistics and machine learning .

Otherwise, it was a good overview of the workflow leading to answer questions with machine learning.

Great overview of most popular data science tools, like Jupyter notebooks and numpy a really great entry point for using machine learning, learning about server services and applying them to businesses.

Very nice course to gain knowledge on different stages of data science Methodology course should be done at the end of the whole certificate course or at least when the student has a better understanding of all the statistical methods available (regression, machine learning..) Found it challenging to follow This is a wonderful course that opened my eyes to Data Science Methodology.

It is a very good course for the beginners as I got all the basic - basic information about the process in data science and machine learning which would be used in the future.

Didn't find enough explanation on Machine Learning Model applied during modeling.

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real world

The content covered on this module is sufficient for a beginner to get and idea of what Data Science Methodology is and how to implement it in real world scenarios.

The course also uses the data science method to solve a real world problem that one may encounter in their career.

It really gives you an insight into the real world problems.

Great real world examples.

It was a bit tough grasping certain concepts Nice explanation I found it a little bit dificult GOOD This incredible course provides me the methods that I can apply to real world problems The final assignment was a bit vague probably due to the choices of subject we were allowed to perform this on.

For a newbie,It is very important to understand how to solve a real world problem and for that its very important you should have knowledge of "How to approach?"

However, to fully understand the topic, need to do more practices and hand-on on the real world project.

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final assessment

Also I only was reviewed by one peer for my final assessment.

The final assessment could have been better, though.

Amazing course with a lot of work to do in the final assessment.

Completing the final assessment was not easy either, because we needed to come up with an own idea and problem.

very good course I've learned a lot i believe the content is targeting more experienced audience, along the course it was bit hard to keep track of all information and the final assessment also aimed for higher level of knowledge I've learned a lot in this course, especially the Data Science framework.

For example, why is feedback not part of the final assessment , where the keywords repeated in the training and in the final assessment?

Falta mas ejemplos descriptivos Great course and easily explaining material The final assessment is very confusing for starters and needs to be more in line with the material actually taught.

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analytic approach

In this case, you need to have a bottom-up approach - play with the data already collected and see which analytic approach is feasible.

I would like to know more about techniques a model statistics to understand more the processes in Analytic approach, data preparation and modeling and apply correctly in a specific situation in a data science project.

Thank you This course was really good with good understanding from Analytic approach till feedback.

A very good course to get the Data Science Methodology:Business Understanding, Analytic Approach, Data Requirements, Data Collection, Data Understanding, Data Preparation, Modeling, Evaluation, Deployment, Feedback.

Perhaps analytic approach and model development and deployment could have used additional modules or case studies.

I think they called it "analytic approach".

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life cycle

Splendid Course, that takes one through the entire Data Science Life Cycle with True details and examples Useful course.

It is a good course, teaching about the general process and life cycle of a data science project.

Nice course Good, coherent explanation and walk-through of the data science development life cycle.

The instructor explains the life cycle and flow of the Data Science methodology along with an example scenario.

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Careers

An overview of related careers and their average salaries in the US. Bars indicate income percentile.

Temporary Data Science Supervisor $49k

Associate Data Science Supervisor $55k

Science writer / data analyst $63k

Coop Data Science Manager $65k

Problem Management Manager $68k

Problem Analyst Consultant $78k

Volunteer Director of Data Science $78k

Supervisor 1 Data Science Supervisor $91k

Retired Data Science Supervisor $96k

Vice Data Science Manager $133k

Assistant Director 1 of Data Science $133k

Owner Director of Data Science $149k

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Rating 4.3 based on 1,643 ratings
Length 4 weeks
Effort 3 weeks of study, 2 - 3 hours/week
Starts Jun 28 (13 weeks ago)
Cost $38
From IBM via Coursera
Instructors Alex Aklson, Polong Lin
Download Videos On all desktop and mobile devices
Language English
Subjects Data Science
Tags Data Science Data Analysis

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