Course

Credit Type:
Course
ACE ID:
IBM-0023
Version:
2
Organization:
Coursera Inc.
Location:
Online
Length:
24 weeks and 96 hours
Minimum Passing Score:
70
ACE Credit Recommendation Period:
Credit Recommendation & Competencies
Level Credits (SH) Subject
Lower-Division Baccalaureate 3 Python Programming Fundamentals
Lower-Division Baccalaureate 3 Database and SQL Fundamentals
Lower-Division Baccalaureate 2 Introduction to Statistical Methods
Lower-Division Baccalaureate 1 Data Science
Description

Objective:

This course is offered through Coursera, which is an ACE Authorized Instructional Platform.

The course objective is for learners to gain the practical knowledge and experience to delve deeper into Data Science and work on more advanced Data Science projects.

The specialization consists of 5 self-paced online modules that provide learners with the foundational skills required for Data Science, including open source tools and libraries, Python, Statistical Analysis, SQL, and relational databases. Students learn these data science pre-requisites through hands-on practice using real data science tools and real-world data sets.

Learning Outcomes:

  • Working knowledge of Data Science Tools such as Jupyter Notebooks, R Studio, GitHub, Watson Studio
  • Statistical Analysis techniques including Descriptive Statistics, Data Visualization, Probability Distribution, Hypothesis Testing and Regression
  • Python programming basics including data structures, logic, working with files, invoking APIs, and libraries such as Pandas and Numpy
  • Relational Database fundamentals including SQL query language, Select statements, sorting and filtering, database functions, accessing multiple tables

General Topics:

  • Data Scientist's Toolkit
  • Open Source Tools
  • IBM Tools for Data Science
  • Final Assignment: Create and Share Your Jupyter Notebook
  • Python Basics
  • Python Data Structures
  • Python Programming Fundamentals
  • Working with Data in Python
  • APIs and Data Collection
  • Crowdsourcing Short Squeeze Dashboard
  • Course Introduction and Python Basics
  • Introduction and Descriptive Statistics
  • Data Visualization
  • Introduction to Probability Distributions
  • Hypothesis Testing Regression Analysis
  • Project Case: Boston Housing Data
  • Getting Started with SQL
  • Introduction to Relational Databases and Tables
  • Intermediate SQL
  • Accessing Databases using Python Course Assignment
  • Bonus Module: Advanced SQL for Data Engineering (Honors)
Instruction & Assessment

Instructional Strategies:

  • Audio Visual Materials
  • Case Studies
  • Computer Based Training
  • Lectures
  • Practical Exercises

Methods of Assessment:

  • Other
  • Quizzes
  • Peer review graded projects with rubrics
Supplemental Materials
Equivalencies

Other offerings from Coursera Inc.

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College Credit Opportunities