Data Science

Data Science is a collaborative effort of talented individuals applying diverse skills and expertise in the areas of data engineering, mathematics, and analysis to solve the world’s most difficult problems for the benefit of all.

The hands-on Data Science course teaches participants to have the skills required to facilitate data-driven business decisions, including:

• Mining data
• Manipulating data
• Visualizing and reporting data
• Applying basic statistical methods
• Analyzing complex datasets while adhering to governance and quality standards throughout the entire data life cycle.

The Data Science program will provide hands-on experience to help obtain fundamental data science techniques using Python and R.  The course covers Data Management, Data Analysis, and Data Visualization utilizing data science techniques with a focus on the completion of a real-world Use Case as part of a collaborative team.

Approach:

A Collaborative Team that fosters cross-training and uses the following “assigned member roles”:

• Project/Security Manager
• System Administration
• Data Engineering
• Data Analysis (Statistics)
• Data Analysis (Mathematics)
• Use-Case driven based on real-world needs.
• Over the last few years more and more commercial organizations are starting to realize the strategic value of data.
• Use Cases are used to prioritize the most critical business areas and build the skills required to quickly begin applying Data Science techniques to solving business problems.

After attending this course, a data scientist will be able to:

• Ask pertinent questions and identify business pain points.
• Apply statistics and computer science, along with business acumen, to data analysis.
• Use a wide range of tools and techniques for preparing and extracting data—everything from databases and SQL to data mining to data integration methods.
• Write programs that automate data processing and calculations.
• Tell—and illustrate—stories that clearly convey the meaning of results to decision-makers and stakeholders at every level of technical understanding.
• Explain how the results can be used to solve business problems.
• Collaborate with other data science team members, such as data and business analysts, IT architects, data engineers, and application developers.

40 hours of virtual, facilitated course time is required.

Training Overview
What is Analytics and Data Science?
Team Dynamics and Selection
Project Management – Agile Methodology
Use Case Methodology
Use Case Overview – Introduction
Corporate Sponsor – Introduction

Managing and Securing Data (Milestone)
What is Data Management?
Data Catalog (Logging)
Data Integrity (Triage)
Data Enrichment (Controls)
What is Data Security?
Information Security Compliance
Policy/Legal Compliance
Access Controls

Build the DSCI Environment
Introduction to Linux
Tool Installation
System Security
System Administration
Access Control
Data Control

Basic Tools
Excel
SQL
Essential Tools
Opensource – Introduction
Python – Introduction
R – Introduction

Analytics & Data Science 
Use Case Overview
Data Exploration
Data Management
Data Ingestion
Data Standardization
Data Summation (Basic Statistics)

Data Modeling and Analysis
Use Case: Hands-on
More Python
More R
Regression (Value Estimation)
Segmentation
Clustering

Advanced Analysis
Decision Trees
Time-Series (Forecasting)
Supervised vs Unsupervised Learning
Sampling and A/B Testing
Use Case: Hands-on
More Python
More R

Visualization and Reporting
Python -Visualization and Reporting Packages
R  – Visualization and Reporting Packages
Use Case: Hands-on
Sensitivity Analysis
Model Refinement

Finalizing the Use Case
Use Case: Hands-on
Presentations
Problem Review
Assumptions Review
Parameter Review
Solution Review
Graphs & Charts
Works Cited
Report Generation

Use Case Presentations by Teams

Data Science has no official certification or exam.

Data Science has no required prerequisites for admittance.

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Students are responsible for purchasing course materials and paying for professional certification exams, if applicable.

*This program is authorized for WIOA funding for eligible applicants. For information, click here.

Maryville Course Fee: $2,000

Estimated course material cost: N/A
Estimated exam fee: N/A
Estimated total cost to complete this course: $2,064