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- Course Introduction
- What is Data Science?
- Fundamentals of Data Science
- The Many Paths to Data Science
- Advice for New Data Scientists
- Lesson Summary: Defining Data Science
- A Day in the Life of a Data Scientist
- Data Science Skills & Big Data
- Understanding Different Types of File Formats
- Data Science Topics and Algorithms
- Lesson Summary: What Do Data Scientists Do?
What is Data Science
Quick Facts
| particular | details | |||
|---|---|---|---|---|
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Medium of instructions
English
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Mode of learning
Self study
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Mode of Delivery
Video and Text Based
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Course overview
The Data Science certification course duration is 11 hours (approximately). This programme is a beginner-level course and candidates can learn at their own pace with flexibility. The course focuses on providing the fundamentals of data science and its significance in today's data-driven world. Students will gain advice from data science professionals and data scientists.
The certification programme equips the students with Data Science, Big Data, Machine Learning, Deep Learning and Data Mining skills. The Data Science certification by Coursera a foundational understanding of the subject or tool. They will also learn new concepts and gain hands-on projects. The course is taught in English but is also available in 22 other languages.
Also Read: Online Data Science And Machine Learning Courses & Certifications
The highlights
- Beginner Level
- 11 Hours Online Course
- Flexible Schedule
- Taught in English/Available in 22 Languages
Program offerings
- Gudiane from data science professionals
- Advice from data scientists
- Shareable certificate
- 23 assessments.
Course and certificate fees
The fees for course What is Data Science is -
Certification | Fee Amount in INR |
What is Data Science (Audit) | Free |
What is Data Science - 1 month | Rs.4,117 /- per month |
What is Data Science - 3 months | Rs.2,745/- per month |
What is Data Science - 6 months | Rs.2,059/- per month |
certificate availability
Yes
certificate providing authority
Coursera
Who it is for
The certification course is designed for aspiring students and working professionals to develop the required knowledge and skills. This course is also useful for:
- Data Scientist
- Data Analyst
What you will learn
After completing the Data Science training, the participants will be equipped with the required skills such as Data Science, Big Data, Machine Learning, Deep Learning and Data Mining. They will also learn about data science and its importance, what data scientists will do, data literacy for data science and applications and careers in data science.
The participants will gain a comprehensive understanding of the various paths to advance a career in data science. Upon the completion of the Data Science Certification syllabus, the students will gain in-depth knowledge of why data science is considered the most in-demand job in the 21st century.
The syllabus
Module 1: Defining Data Science and What Data Scientists Do
Videos
Readings
- Course Syllabus
- Professional Certificate Career Support
- Helpful Tips for Course Completion
- Lesson Overview: Defining Data Science
- Lesson Overview: What Do Data Scientists Do?
- Summary: What Do Data Scientists Do?
Assignments
- Graded Quiz: Defining Data Science
- Graded Quiz: What Data Scientists Do
- Practice Quiz: Data Science: The Sexiest Job in the 21st Century
- Practice Quiz: Defining Data Science
- Practice Quiz: What makes Someone a Data Scientist?
Discussion prompt
- Introduce Yourself
Plugins
- Data Science: The Sexiest Job in the 21st Century
- Glossary: Defining Data Science
- What Makes Someone a Data Scientist?
- Glossary: What do Data Scientists Do?
Module 2: Data Science Topics
Videos
- How Big Data is Driving Digital Transformation
- Introduction to Cloud
- Cloud for Data Science
- Foundations of Big Data
- Data Science and Big Data
- What is Hadoop?
- Big Data Processing Tools: Hadoop, HDFS, Hive, and Spark
- Lesson Summary: Big Data and Data Mining
- Artificial Intelligence and Data Science
- Generative AI and Data Science
- Neural Networks and Deep Learning
- Applications of Machine Learning
- Lesson Summary: Deep Learning and Machine Learning
Readings
- Lesson Overview: Big Data and Data Mining
- Lesson Overview: Deep Learning and Machine Learning
- Summary: Deep Learning and Machine Learning
Assignments
- Graded Quiz: Big Data and Data Mining
- Graded Quiz: Deep Learning and Machine Learning
- Practice Quiz: Data Mining
- Practice Quiz: Big Data and Data Mining
- Practice Quiz: Regression
- Practice Quiz: Deep Learning and Machine Learning
Plugins
- Data Mining
- Glossary: Big Data and Data Mining
- Regression
- Lab: Exploring Data using IBM Cloud Gallery
- Glossary: Deep Learning and Machine Learning
Module 3: Applications and Careers in Data Science
Videos
- How Should Companies Get Started in Data Science?
- Old Problems, New Data Science Solutions
- Applications of Data Science
- How Data Science is saving lives
- Lesson Summary: Data Science Applications Domain
- How Can Someone Become a Data Scientist?
- Recruiting for Data Science
- Careers in Data Science
- Importance of Mathematics and Statistics for Data Science•
- Lesson Summary: Careers and Recruiting in Data Science
Readings
- Lesson Overview: Data Science Application Domains
- Lesson Overview: Careers and Recruiting in Data Science
- Summary: Careers and Recruiting in Data Science
- A Roadmap to your Data Science Journey
- Course Summary
- Congrats & Next Steps
- Course Team and Acknowledgements
- IBM Digital Badge
Assignments
- Graded Quiz: Data Science Application Domains
- Graded Quiz: Careers and Recruiting in Data Science
- Quiz Based on Case Study
- Final Exam
- Practice Quiz: The Final Deliverable
- Practice Quiz: Data Science Application Domains
- Practice Quiz: The Report Structure
- Practice Quiz: Careers and Recruiting in Data Science
Plugins
- The Final Deliverable
- Glossary: Data Science Application Domains
- The Report Structure
- Glossary: Careers and Recruiting in Data Science
- Case Study: Final Assignment
- Explore Data Science Job Listings
Module 4: Data Literacy for Data Science (Optional)
Videos
- Understanding Data
- Data Sources
- Viewpoints: Working with Varied Data Sources and Types
- Lesson Summary: Understanding Data
- Data Collection and Organization
- Relational Database Management System
- NoSQL
- Data Marts, Data Lakes, ETL, and Data Pipelines
- Viewpoints: Considerations for Choice of Data Repository
- Data Integration Platforms
- Lesson Summary: Welcome to Data Literacy
Readings
- Lesson Overview: Understanding Data
- Lesson Overview: Data Literacy
- Summary: Data Literacy for Data Science
Assignments
- Practice Quiz: Metadata
- Practice Quiz - Understanding Data
- Practice Quiz: Data integration Platforms
- Practice Quiz: Data Literacy
Plugins
- Reading: Metadata
- Glossary: Understanding Data
- Glossary: Data Literacy for Data Science
Instructors
Mr Rav Ahuja
Global Program Director
IBM
B.E /B.Tech, MBA
Mr Alex Aklson
Data Scientist
IBM
Ph.D
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