4.6
stars
18,788 ratings

Alex Aklson +1 more instructor

228,580 already enrolled

Offered By

Part of the Bachelor of Applied Arts and Sciences degree
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IBM Skills Network

About this Course

286,204 recent views

If there is a shortcut to becoming a Data Scientist, then learning to think and work like a successful Data Scientist is it. Most of the established data scientists follow a similar methodology for solving Data Science problems.  In this course you will learn and then apply this methodology that can be used to tackle any Data Science scenario.  
The purpose of this course 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 practicing data science 
- Forming a business/research problem, collecting, preparing & analyzing data, building a model, 
  deploying a model and understanding the importance of feedback  
- Apply the 6 stages of the CRISP-DM methodology, the most popular methodology for Data Science and Data Mining problems 
- How data scientists think! 

To apply the methodology, you will work on a real-world inspired scenario and work with Jupyter Notebooks using Python to develop hands-on experience.

Flexible deadlines

Reset deadlines in accordance to your schedule.

Shareable Certificate

Earn a Certificate upon completion

100% online

Start instantly and learn at your own schedule.

Coursera Labs

Includes hands on learning projects.

Learn more about Coursera Labs

Beginner Level

No previous experience required, although prior use of Jupyter Notebooks will be beneficial.

Approx. 8 hours to complete

English

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What you will learn

Describe what a methodology is and why data scientists need a methodology.
Apply the six stages in the Cross-Industry Process for Data Mining (CRISP-DM) methodology to analyze a case study.
Determine an appropriate analytic model including predictive, descriptive, and classification models to analyze a case study.
Decide on appropriate sources of data for your data science project.

Skills you will gain

Data Science
Methodology
CRISP-DM
Data Analysis
Data Mining

Flexible deadlines

Reset deadlines in accordance to your schedule.

Shareable Certificate

Earn a Certificate upon completion

100% online

Start instantly and learn at your own schedule.

Coursera Labs

Includes hands on learning projects.

Learn more about Coursera Labs

Beginner Level

No previous experience required, although prior use of Jupyter Notebooks will be beneficial.

Approx. 8 hours to complete

English

Could your company benefit from training employees on in-demand skills?

Try Coursera for Business

Instructors

Instructor rating

4.59/5 (1,832 Ratings)

Alex Aklson

Ph.D., Data Scientist

803,575 Learners

22 Courses

Polong Lin

Data Scientist

238,942 Learners

6 Courses

Offered by

IBM Skills Network

IBM is the global leader in business transformation through an open hybrid cloud platform and AI, serving clients in more than 170 countries around the world. Today 47 of the Fortune 50 Companies rely on the IBM Cloud to run their business, and IBM Watson enterprise AI is hard at work in more than 30,000 engagements. IBM is also one of the world’s most vital corporate research organizations, with 28 consecutive years of patent leadership. Above all, guided by principles for trust and transparency and support for a more inclusive society, IBM is committed to being a responsible technology innovator and a force for good in the world.

Start working towards your Bachelor's degree

This course is part of the 100% online Bachelor of Applied Arts and Sciences from IBM Skills Network. If you are admitted to the full program, your courses count towards your degree learning.

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Syllabus - What you will learn from this course

Content Rating93%(19,885 ratings)

Week1

Week 1

3 hours to complete

From Problem to Approach and From Requirements to Collection

In this module, you will learn about why we are interested in data science, what a methodology is, and why data scientists need a methodology. You will also learn about the data science methodology and its flowchart. You will learn about the first two stages of the data science methodology, namely Business Understanding and Analytic Approach. Finally, through a lab session, you will also obtain how to complete the Business Understanding and the Analytic Approach stages and the Data Requirements and Data Collection stages pertaining to any data science problem.

3 hours to complete

5 videos (Total 19 min), 3 readings, 4 quizzes

Week2

Week 2

3 hours to complete

From Understanding to Preparation and From Modeling to Evaluation

In this module, you will learn what it means to understand data, and prepare or clean data. You will also learn about the purpose of data modeling and some characteristics of the modeling process. Finally, through a lab session, you will learn how to complete the Data Understanding and the Data Preparation stages, as well as the Modeling and the Model Evaluation stages pertaining to any data science problem.

3 hours to complete

6 videos (Total 22 min), 3 readings, 4 quizzes

Week3

Week 3

2 hours to complete

From Deployment to Feedback

2 hours to complete

3 videos (Total 10 min), 2 readings, 3 quizzes

Reviews

4.6

2357 reviews

5 stars
71.23%
4 stars
21.48%
3 stars
4.88%
2 stars
1.52%
1 star
0.87%

TOP REVIEWS FROM DATA SCIENCE METHODOLOGY

by JMFeb 26, 2020

Very informative step-by-step guide of how to create a data science project. Course presents concepts in an engaging way and the quizzes and assignments helped in understanding the overall material.

by TMJun 18, 2021

Very interesting course. It shed a light on what the structured approach really is. It's worth to pause for a moment with every step of the methodology and think how to apply it in real life. Thanks!

by HHAug 16, 2020

Very enriching course. I really liked the content of this course as it has guided me the basic framework of solving any data science problem. the assignment is also fun and enjoyable to do.

by SJAug 8, 2018

This is my favourite in the series, the 10 questions to be answered were mind opening. The repetition after every video makes easier for important points to stick to the brain. Very good indeed...

View all reviews

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Data Science Methodology

About this Course

What you will learn

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