Data Science


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Course Overview

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 worlds most difficult problems for the benefit of all.

Course NameStart DateEnd DateDaysTimeSession DatesTuitionHoursRegister
Data ScienceNovember 7, 2022December 12, 2022Mon, Wed6:00 PM - 10:00 PM11/7, 11/9, 11/14, 11/16, 11/21, 11/28, 11/30, 12/5, 12/7, 12/12$1,900.0040
Data ScienceJanuary 10, 2023February 9, 2023Tue, Thur6:00 PM - 10:00 PM1/10, 1/12, 1/17, 1/19, 1/24, 1/26, 1/31, 2/2, 2/7, 2/9$1,900.0040

Who this course is for:

This course is best suited for IT Professionals and also IT Managers who would like to learn data science fundamentals using Python and R.

What you’ll learn

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.

Course Outline

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
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)

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
Problem Review
Assumptions Review
Parameter Review
Solution Review
Graphs & Charts
Works Cited
Report Generation

Use Case Presentations by Teams

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