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Workforce Development & Community Education - Fall 2024 - Summer 2025 - NON-CREDIT CATALOG
Introduction to Data Science and Machine Learning
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 Return to: Areas of Study
Overview
Data science is an exciting discipline, which leverages Machine Learning and Artificial Intelligence to enable decision makers to turn raw data into understanding, insight, and actionable options. With the enormous volume and variety of data being created and collected daily, Data Science is one of today’s fastest growing and critically important fields for businesses, organizations, and government. Data Scientists are in demand by both industry and the public sector with robust job growth expected well into the next decade.
Target Audience:
Information Architects, Data Analysts, Statisticians, Developers, Business Intelligence professionals, Business Analysts, Big Data specialists, Coders, Web Developers, learners interested in Predictive Analytics and anyone looking to expand their skills and / or advance their career by learning these valuable and in demand knowledge areas.
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Program Description
This hands on, project-based course aims to serve as a foundation for building real world applications with Machine Learning capabilities and as a starting point for a career as a well-rounded data practitioner. The course is offered in three successive modules: fundamentals, deep learning, and CompTIA DataX.
The fundamentals module focuses on key foundational concepts related to Data Science and Machine Learning using the Python programming language. Students will learn the fundamentals of problem solving, statistical algorithms, and basic machine learning models using Jupyter Notebooks within the Anaconda development environments.
The deep learning module focuses on implementing algorithms using the Python programming language and the PyTorch and Tensorflow deep learning libraries to implement projects related to classification, image recognition and natural language processing using the Anaconda and Google Colab development environments.
The CompTIA DataX module supplements and extends the prior modules and will help prepare the student to pass the CompTIA DataX (DY0-001) Certification Exam. This certification can broaden knowledge for a diverse range of career paths, creating opportunities for advancement and specialization in the rapidly evolving data science industry. With CompTIA DataX, possible career paths include data scientist, quantitative analyst, machine learning engineer/specialist, predictive analyst, and artificial intelligence (AI) engineer.
Objective:
After taking this class, students are expected to:
- Understand fundamentals of the Python programming language and create scripts that interact with data sets and machine learning models,
- Interact with data sets in various formats and create meaningful visualizations based on business requirements,
- Understand the basics of Python-based machine learning models and when to select the appropriate algorithms based on business requirements,
- Gain proficiency with the Anaconda Data Science Platform and Jupyter Notebooks
- Understand the foundations of how Deep Learning is associated with human brain function
- Implement classification models using Deep Learning algorithms
- Implement image recognition models using Deep Learning algorithms
- Implement natural language processing models using Deep Learning algorithms
- Illustrate the data science lifecycle
- Analyze business problems and ad communicate for business impact
- Collect, clean, prepare and explore data
- Navigate the model selection process
- Employ machine learning methods
- Evaluate and refine data models
- Deploy data models
- Discover specialized data science applications
Course Outline:
- Class Introduction and Course Topics Review
- Overview with Data Sets, Python and Jupyter Notebooks
- Transform and Visualize Datasets (Including CSV and JSON)
- Implement Data Wrangling Techniques
- Introduction to Statistical Analysis
- Implement Regression, Classification and Clustering Models
- Understand Deep Learning Fundamentals
- Understand Deep Neural Networks
- Understand Model Loss, Optimizers and Learning Rates
- Understand the NLTK Libraries
- Implement a Classification Model Using Deep Learning
- Implement Deep Learning Models for Image Recognition and Natural Language Processing
- Recognize Lifecycle Frameworks
- Identify Tools and Best Practices
- Recognize the Importance of Data Privacy and Security
- Explain the Basics of Time Series
- Demonstrate Exploratory Data Analysis
- Explore Mathematical Areas
- Address Research Questions Requiring Causal Explanation
- Tune Hyperparameters
- Prepare Data for Stakeholders
- Deliver the Data Story
- Describe Deployment Methodologies
- Decipher ML Ops
- Perform Graph Analytics
- Evaluate Techniques for Unique Events
Spring Course Offerings
Introduction to Data Science and Machine Learning. REMOTE, CE-COMP 2239
1/21/2025 to 5/29/2025 (Tuesday / Thursday evenings), 6:00 pm to 9:00 pm, $ 2,795. #47485
How to Register
Register over the phone using MC, Visa or Discover. Call 914-606-6830.
You will need the Class # when speaking with a representative.
Office hours for registration are Monday – Thursday 8:30 a.m. to 7:15 p.m.
Friday 8:30 a.m. to 4:30 p.m. (in summer, 9:00 a.m. – 12:00 noon)
Saturday 9:00 a.m. to 3:30 p.m. (in summer, closed some Saturdays)
For course questions, please contact:
Romina Ganopolsky, Program Specialist, Professional Development Center: Call 914-606-5685 or email romina.ganopolsky@sunywcc.edu
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Return to: Areas of Study
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