Data Science Methodology
Master the essential CRISP-DM methodology and foundational approaches to solve real-world data science problems effectively.
Master the essential CRISP-DM methodology and foundational approaches to solve real-world data science problems effectively.
This course cannot be purchased separately - to access the complete learning experience, graded assignments, and earn certificates, you'll need to enroll in the full IBM Data Science Professional Certificate program. You can audit this specific course for free to explore the content, which includes access to course materials and lectures. This allows you to learn at your own pace without any financial commitment.
4.6
(20,241 ratings)
3,10,844 already enrolled
Instructors:
Polong Lin
English
پښتو, বাংলা, اردو, 4 more
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What you'll learn
Apply the six stages of CRISP-DM methodology
Determine appropriate analytic approaches for problems
Identify and evaluate data sources effectively
Develop systematic problem-solving strategies
Create effective data science solutions
Skills you'll gain
This course includes:
1 Hours PreRecorded video
11 assignments
Access on Mobile, Tablet, Desktop
FullTime access
Shareable certificate
Top companies offer this course to their employees
Top companies provide this course to enhance their employees' skills, ensuring they excel in handling complex projects and drive organizational success.
There are 4 modules in this course
This foundational course introduces learners to key data science methodologies, focusing on the CRISP-DM (Cross-Industry Process for Data Mining) framework. Students learn the systematic approach to data science projects from business understanding to deployment and feedback. The curriculum covers essential stages including problem formulation, data requirements, preparation, modeling, evaluation, and deployment. Through hands-on labs using Python in Jupyter Notebooks, learners apply these methodologies to real-world scenarios.
From Problem to Approach and From Requirements to Collection
Module 1 · 1 Hours to complete
From Understanding to Preparation and From Modeling to Evaluation
Module 2 · 1 Hours to complete
From Deployment to Feedback and Final Evaluation
Module 3 · 0 Hours to complete
Final Project and Assessment
Module 4 · 1 Hours to complete
Fee Structure
Instructors
Dr. Alex Aklson: Crafting Data-Driven Solutions and Innovating Smart Health Systems at IBM
Dr. Alex Aklson is a data scientist in IBM Canada’s Digital Business Group, where he has contributed to innovative projects, including the development of a smart system to detect early signs of dementia by analyzing walking speed and home activity patterns in older adults. Prior to IBM, Alex worked at Datascope Analytics in Chicago, where he crafted data-driven solutions using a human-centered approach. He holds a Ph.D. in Biomedical Engineering from the University of Toronto.
Polong Lin
4.6 rating
2,275 Reviews
3,33,885 Students
6 Courses
Advocate for Data Science and AI Education
Polong Lin is a dedicated Data Scientist at IBM, where he focuses on data science advocacy and partnerships. As a co-founder of the IBM Data Science Bootcamp, he is committed to enhancing education in the field of data science and making it more accessible to aspiring professionals. Polong also leads Canada's largest data science meetup group in Toronto, fostering a vibrant community for knowledge sharing and collaboration among data enthusiasts. His extensive experience in the tech industry includes roles where he has successfully bridged the gap between technical concepts and practical applications, empowering individuals and organizations to leverage data effectively. Passionate about democratizing data science, Polong actively engages in speaking events and workshops, inspiring others to explore the transformative potential of artificial intelligence and machine learning.
Testimonials
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4.6 course rating
20,241 ratings
Frequently asked questions
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