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IBM Online Courses
Data Science Methodology

Data Science Methodology

Gain the critical skills you need to tackle problems effectively. Learn how to solve problems through analyzing data to address real-world business scenarios.

Develop your skills in this critical aspect of data science and take a great step forward in your data science career.

Data Science Methodology Highlights

  Course duration

Duration

  • 5 weeks, online
    2 hrs/week
   Course Fee

Fee

US$ 99 - US$ 199
Course duration

Duration

  • 5 weeks, online
    2 hrs/week
Course Fee

Fee

US$ 99 - US$ 199

The data a business holds is a valuable asset. Through careful data analysis conducted utilizing proven methodologies, organizations can gain important insights that give them a competitive edge. To achieve this, data scientists must have a firm understanding of what questions to ask in the first place, as well as the necessary knowledge of how to analyze the data. Developing strong competencies in these areas is critical, therefore, for a successful career in data science.

During this course, you will be introduced to the major steps required for tackling a data science problem. You will learn about the key stages in data science methodology. You will develop your understanding of which methodologies are used for different analytic approaches. You will discover how to solve data science problems and come to appreciate the value and purpose of data modeling. And you will explore the characteristics of the modeling process, what happens after model deployment, and the importance of model feedback.

Having a firm grasp of data science methodology is critical for a career in this field. In this course, you will develop the skills you need to ensure the data you are using is both relevant and properly manipulated in order to address business and real-world challenges.

This FutureSkills Prime/IBM course comprises five purposely designed modules that take you on a carefully defined learning journey.

It is a self-paced course, which means it is not run to a fixed schedule with regard to completing modules or submitting assignments. To give you an idea of how long the course takes to complete, it is anticipated that if you work 2 hours per week, you will complete the course in 5 weeks. However, as long as the course is completed by the end of your enrollment, you can work at your own pace. And don’t worry, you’re not alone! You will be encouraged to stay connected with your learning community and mentors through the course discussion space.

The materials for each module are accessible from the start of the course and will remain available for the duration of your enrollment. Methods of learning and assessment will include videos, reading material, and online exam questions.

As part of our mentoring service you will have access to valuable guidance and support throughout the course. We provide a dedicated discussion space where you can ask questions, chat with your peers, and resolve issues. Depending on the payment plan you have chosen, you may also have access to live classes and webinars, which are an excellent opportunity to discuss problems with your mentor and ask questions. Mentoring services will vary across packages.

Once you have successfully completed the course, you will earn your Certificate of Completion. You will also receive an IBM Certificate.

You will be able to:

  • Tackle a data science problem.
  • Understand why data scientists need a methodology and an approach.
  • Understand how to prepare and clean data.
  • Form a concrete business question or research.
  • Individuals seeking to understand the fundamentals of dealing with a data science problem.
  • Individuals seeking to understand the process of resolving a data science query.
  • Individuals seeking to understand models for solving a data science problem.

No experience required.

This course is aligned with industry-approved occupational standards set by SSC NASSCOM. Once you’ve successfully completed this course, you will receive a Certificate of Completion that confirms you have:

  • Job-ready competencies
  • Practical experience
  • Assessed technical knowledge

The national occupational standards to which this course is aligned relates to the following job roles:

  • Business Intelligence Analyst 
  • Data Scientist

Course Outline

Welcome!

Welcome! (4:01)

Welcome! (4:01)

About this course

General Information

General Information

Learning Objectives

Learning Objectives

Syllabus

Syllabus

Grading Scheme

Grading Scheme

Change Log

Change Log

Copyrights and Trademarks

Copyrights and Trademarks

Module 1 - From Problem to Approach

Learning Objectives

Learning Objectives

Business Understanding (5:02)

Business Understanding (5:02)

Analytic Approach (3:23)

Analytic Approach (3:23)

Lab - From Problem to Approach

Lab - From Problem to Approach

Graded Review Questions

Graded Review Questions (3 Questions) Review Questions

Module 2 - From Requirements to Collection

Learning Objectives

Learning Objectives

Data Requirements (3:28)

Data Requirements (3:28)

Data Collection (2:54)

Data Collection (2:54)

Lab - From Requirements to Collection

Lab - From Requirements to Collection in R

Graded Review Questions

Graded Review Questions (3 Questions) Review Questions

Module 3 - From Understanding to Preparation

Learning Objectives

Learning Objectives

Data Understanding (3:16)

Data Understanding (3:16)

Data Preparation (7:16)

Data Preparation (7:16)

Lab - From Understanding to Preparation

Lab - From Understanding to Preparation in R Bookmark this page

Graded Review Questions

Graded Review Questions (3 Questions) Review Questions

Module 4 - From Modeling to Evaluation

Learning Objectives

Learning Objectives

Modeling (6:11)

Modeling (6:11)

Evaluation (3:57)

Evaluation (3:57)

Lab - From Modeling to Evaluation

Lab - From Modeling to Evaluation in R

Graded Review Questions

Graded Review Questions (3 Questions) Review Questions

Module 5 - From Deployment to Feedback

Learning Objectives

Learning Objectives

Deployment (3:31)

Deployment (3:31)

Feedback (3:08)

Feedback (3:08)

Graded Review Questions

Graded Review Questions (3 Questions) Review Questions

Course Summary

Course Summary (3:25)

Course Summary (3:25)

Final Exam

Instructions

Instructions

Final Exam

Final Exam (20 Questions) Timed Exam Final Exam

Certificates

Certificates

Certificates
Course Certificate

Earn your certificate

Once you have completed this course, you will earn your certificate.

Preview digital certificate
Data Science Methodology

Course details

Course Certificate

Certificate

  • IBM Certificate
  • Certificate of Participation
About Course

About this course

  • 05 Modules
  • 01 Skill
Course Includes

Includes

  • 01 Final exam
  • 05 Quizzes
  • 12 Videos
Course Exercises

Exercises to explore

  • Python
  • Jupyter notebook
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FAQs

Data science is a field that integrates programming tools, statistical analysis, algorithms, and machine learning concepts in order to extract useful insights from massive amounts of data. It entails applying a range of disciplines, including statistics, scientific techniques, artificial intelligence (AI), and data analysis.

During this course you will learn:

  • The most important steps in solving a data science problem.
  • The primary phases involved in data science practice, from defining a specific business or research challenge to collecting and analyzing data, constructing a model, and comprehending the feedback received after model deployment.
  • To think like a data scientist.

Job roles in data science include:

Data Analyst

A data analyst examines data and draws conclusions from their results. They assist in the development of a comprehensive picture of the company's market position through data extraction, data cleansing, and first-data analysis using high-tech computer models. They also evaluate data quality and report back to management on their findings.

Data Engineers

Data engineers are the backbone of a business because they are in charge of database design and management. They supervise the installation of data pipelines and ensure that information is sent to the appropriate departments. They also work with other data experts and use data visualization to convey their results with the rest of the company.

Business Intelligence Analyst

A business intelligence analyst examines data to help a company become more productive and efficient. They know how to use a variety of specialized machines and tools. They also serve as a link between business and technology, assisting both in achieving better results.

Marketing Analyst

A marketing analyst assists the marketing department of a corporation. They conduct research and provide recommendations on what should be mass-produced versus what should be scrapped. Customer satisfaction surveys are also used to improve present products and services, as well as to identify new things to sell to target clients.

Yes, it is a self-paced course that you can do at your own pace. It does not follow a predetermined timetable, unlike scheduled live sessions. You are free to work at your own pace if you complete the modules and the course before the deadline. 

Yes. Data science methodology is a 100% online course. You will therefore need a good connection to the internet in order to be able to access the course materials.