Course description
Introduction to Data Science Specialization
Interested in learning more about data science, but don’t know where to start? This 4-course Specialization from IBM will provide you with the key foundational skills any data scientist needs to prepare you for a career in data science or further advanced learning in the field.
This Specialization will introduce you to what data science is and what data scientists do. You’ll discover the applicability of data science across fields, and learn how data analysis can help you make data driven decisions. You’ll find that you can kickstart your career path in the field without prior knowledge of computer science or programming languages: this Specialization will give you the foundation you need for more advanced learning to support your career goals.
You’ll grasp concepts like big data, statistical analysis, and relational databases, and gain familiarity with various open source tools and data science programs used by data scientists, like Jupyter Notebooks, RStudio, GitHub, and SQL. You'll complete hands-on labs and projects to learn the methodology involved in tackling data science problems and apply your newly acquired skills and knowledge to real world data sets.
In addition to earning a Specialization completion certificate from Coursera, you’ll also receive a digital badge from IBM recognizing you as a specialist in data science foundations.
This Specialization can also be applied toward the IBM Data Science Professional Certificate.
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Upcoming start dates
Suitability - Who should attend?
No prior experience required.
Outcome / Qualification etc.
All courses in the specialization contain multiple hands-on labs and assignments to help you gain practical experience and skills with a variety of data sets and tools like Jupyter, GitHub, and R Studio. Build your data science portfolio from the artifacts you produce throughout this program. Course-culminating projects include:
- Creating and sharing a Jupyter Notebook containing code blocks and markdown
- Devising a problem that can be solved by applying the data science methodology and explain how to apply each stage of the methodology to solve it
- Using SQL to query census, crime, and demographic data sets to identify causes that impact enrollment, safety, health, and environment ratings in schools
What You Will Learn
- Describe what data science and machine learning are, their applications & use cases, and various types of tasks performed by data scientists
- Gain hands-on familiarity with common data science tools including JupyterLab, R Studio, GitHub and Watson Studio
- Develop the mindset to work like a data scientist, and follow a methodology to tackle different types of data science problems
- Write SQL statements and query Cloud databases using Python from Jupyter notebooks
Skills You Will Gain
- Data Science
- Relational Database Management System (RDBMS)
- Cloud Databases
- Python Programming
- SQL
- Deep Learning
- Machine Learning
- Big Data
- Data Mining
- Github
- Jupyter notebooks
- Rstudio
Training Course Content
- What is Data Science?
- Tools for Data Science
- Data Science Methodology
- Databases and SQL for Data Science with Python
Course delivery details
This course is offered through IBM Skills Network, a partner institute of Coursera.
Suggested pace of 4 hours/week
Expenses
Please visit the Institute website for more information about tuition fees