Online Data Science Certificate

Program Overview

La Salle University's Data Science Certificate is a career-boosting program designed to enhance programming abilities and integrate statistical analysis and data preparation skills. This flexible online program offers multiple start dates per year, making it ideal for working adults. The program emphasizes applicable, career-ready skills, including mobile development, database services, and web solutions, preparing graduates for success in the data-driven IT field.

Program Outline

Degree Overview:

The Data Science Certificate at La Salle University is a career-boosting program designed to enhance your real-world programming abilities.

This online program offers flexibility and convenience with multiple start dates per year, making it ideal for working adults.

Objectives:

• Gain proficiency in programming skills.
• Integrate statistical analysis and data preparation into your skillset.
• Present data-driven results visually.
• Expand your understanding of data science across various fields, including mobile development, database services, and web solutions.
• Learn how these diverse systems interact and work together.

Program Description:

This online program provides a comprehensive understanding of data science, equipping you with the skills to tackle real-world data challenges.

The curriculum includes mobile development, database services, enterprise and web solutions, and demonstrates how these systems integrate and operate together.

The program's emphasis on

applicable, career-ready skills The acquired knowledge can be further applied towards a master's degree.

Other:

• affordable, pay-by-the-course tuition
• All program and course fees are included in the total tuition cost.
• Coursework can be applied towards a master's degree.

Outline:

Program Structure:

• Maximum of 5 courses (15 credit hours).
• Flexible format with multiple start dates per year.

Course Schedule:

• Spring II: March 18th - May 9th
• Summer I: May 20th - July 14th
• Fall I: August 26th - October 20th
• Fall II: October 21st - December 15th

Modules:

• Data Processing and Database Management (CIS 523) - Analyzes and evaluates database designs tied to project strategies.
Covers topics like database systems, architectures, data-definition languages, data-manipulation languages, logical and physical design, models, normalization, integrity, query languages (including SQL), relational algebra, social and ethical considerations, and data privacy.
• Data Mining (CIS 658) - Introduces data mining techniques, specifically focusing on Machine Learning algorithms.
Covers conceptual clustering, learning decision rules and decision trees, case-based reasoning, Bayesian analysis, genetic algorithms, neural networks, data preparation, and result analysis.
• Data Analysis with R (CIS 633) - Teaches students the R programming language and its applications for data exploration and analysis.
Focuses on R utilization for finding interesting features in data and demonstrating data findings effectively to non-technical audiences. Introduces modeling and simulation concepts, including basic queueing theory, the role of random numbers, and identifying probability distribution inputs.
• Artificial Intelligence (CIS 654) - Introduces the field of artificial intelligence (AI), exploring how big data and data mining techniques are used by machines to create AI models for various applications.
Discusses the history, current applications, and future of AI, along with the benefits and risks associated with its development. Covers ethical considerations, privacy, machine bias, neuromorphic computing, Open Neural Network Exchange (ONNX), and data analytics.
• Electives - Choose one of the following courses:
Applies realistic data-driven case studies to demonstrate statistical methodology usage for prediction generation and decision making. Covers topics like applied probability, probability distributions, sampling, estimation, confidence intervals, hypothesis testing, linear and multiple regression, analysis of variance, and model building. Utilizes technology like spreadsheets and dedicated statistical software. Addresses goals like revenue increase, cost reduction, and operation efficiency improvement. Students learn model identification, formulation, and solution methods. Focuses on linear programming (networks and integer programs), the simplex method, forecasting, inventory management, queueing models, and Markov chains. Covers sensitivity analysis, duality, decision analysis, and dynamic programming. Uses spreadsheets and a computer algebra system to expedite analysis processes.
• Web Services Development (CIS 626) - Focuses on developing web services for diverse web applications.
Develops basic programming techniques for server-side application functionality. Uses a non-Windows interface for tools.
• Web Database Development Services (CIS 627) - Covers programming models for database access, including ADO.NET.
Includes client/server, multitiered architectures, database application development, internet and intranet database design and implementation, database-driven websites, and XML syntax related to databases. Examines data privacy and protection on servers. Assessment: Teaching: Careers: Other: La Salle University is ranked in the top 50 percent of national universities nationwide by U.S. News & World Report (2023).

Summary:

The Data Science Certificate program at La Salle University is a comprehensive and career-oriented program designed to equip students with the necessary skills to thrive in the evolving world of data science. The program offers a flexible format, experienced faculty, and a focus on real-world application, making it a valuable option for working adults seeking to advance their careers in the data-driven landscape.

Tuition Fees and Payment Information:

Total Tuition: $15,225 Per Credit Hour: $1,015