Data Science Fundamentals with Python and SQL Specialization
Course Features
Duration
6 months
Delivery Method
Online
Available on
Limited Access
Accessibility
Desktop, Laptop
Language
English
Subtitles
English
Level
Beginner
Effort
3 hours per week
Teaching Type
Self Paced
Course Description
Course Overview
International Faculty
Case Based Learning
Post Course Interactions
Case Studies,Hands-On Training,Instructor-Moderated Discussions
Skills You Will Gain
Prerequisites/Requirements
Just basic computer literacy and willingness to self-learn online.
No prior knowledge of computer science or programming languages required
What You Will Learn
Working knowledge of Data Science Tools such as Jupyter Notebooks, R Studio, GitHub, Watson Studio
Python programming basics including data structures, logic, working with files, invoking APIs, and libraries such as Pandas and Numpy
Statistical Analysis techniques including Descriptive Statistics, Data Visualization, Probability Distribution, Hypothesis Testing and Regression
Relational Database fundamentals including SQL query language, Select statements, sorting & filtering, database functions, accessing multiple tables
Course Content
Module 1: Tools for Data Science
1. What are some of the most popular data science tools, how do you use them, and what are their features? In this course, you'll learn about Jupyter Notebooks, JupyterLab, RStudio IDE, Git, GitHub, and Watson Studio. You will learn about what each tool is used for, what programming languages they can execute, their features and limitations. With the tools hosted in the cloud on Skills Network Labs, you will be able to test each tool and follow instructions to run simple code in Python, R or Scala. To end the course, you will create a final project with a Jupyter Notebook on IBM Watson Studio and demonstrate your proficiency preparing a notebook, writing Markdown, and sharing your work with your peers.
Course Instructors
Aije Egwaikhide
Senior Data Scientist
Svetlana Levitan
Senior Developer Advocate with IBM Center for Open Data and AI Technologies
Romeo Kienzler
Chief Data Scientist, Course Lead
Joseph Santarcangelo
Ph.D., Data Scientist at IBM