Computer Science Courses and Certifications

Introduction to Domain Models

Explore domain modeling, object-oriented paradigm, and visual programming techniques to design and implement software solutions for real-world business problems.

• Coursera
• 9 hours 52 minutes
• Self-Paced
• Paid Course

Clemson University

Applied Data Science

Discover how to extract knowledge from complex data sets using tools from computer science, statistics, visualization, and social sciences, illustrated with real-world case studies.

• Coursera
• 20 hours 52 minutes
• Self-Paced
• Paid Course

Machine Learning for Healthcare Professionals

Explore data mining in healthcare, from theoretical foundations to practical applications, focusing on real-world problem-solving using contemporary software and basic programming skills.

• Coursera
• 12 hours 8 minutes
• Self-Paced
• Paid Course

Workflow and File Management in Lightroom Desktop

Workflow and File Management in Lightroom Desktop with Jared Platt

• CreativeLive
• 55 minutes
• On-Demand
• Paid Course

Data Structures & Algos: Software Development Skills

Master fundamental algorithms and data structures through hands-on exploration of computational problem-solving, complexity analysis, stable matching, sorting techniques, and algorithm optimization for real-world applications.

• Coursera
• 18 hours 48 minutes
• Self-Paced
• Paid Course

Data Management for Analytics Part 1

Master database fundamentals, ER modeling, UML, relational design, and normalization to build robust data management systems supporting analytics and AI applications.

• Coursera
• 9 hours 6 minutes
• Self-Paced
• Paid Course

Introduction to Machine Learning and Algorithmic Bias

Explore AI and machine learning fundamentals while mastering algorithmic bias detection and mitigation strategies for responsible business applications.

• Coursera
• 6 hours 48 minutes
• Self-Paced
• Paid Course

Machine Learning with Small Data Part 1

Discover modern deep learning techniques for training effective models with limited datasets, addressing challenges in healthcare, military, and industry applications.

• Coursera
• 14 hours 21 minutes
• Self-Paced
• Paid Course

Machine Learning for Engineers: Algorithms and Applications

Master practical machine learning algorithms through hands-on implementation in Python and PyTorch, covering supervised and unsupervised learning techniques for real-world applications in computer vision, NLP, and robotics.

• Coursera
• 17 hours 31 minutes
• Self-Paced
• Paid Course

Machine Learning and Data Analytics Part 1

Dive into data mining fundamentals, exploring preprocessing, classification, clustering, and regression techniques through hands-on projects and real-world case studies.

• Coursera
• 15 hours 20 minutes
• Self-Paced
• Paid Course

UI/UX Design Principles

Master essential UI/UX principles, from wireframing to prototyping, while learning to create accessible, responsive designs and leverage Microsoft Copilot for enhanced CSS workflows.

• Coursera
• 1 day 5 hours 1 minute
• Self-Paced
• Paid Course

Program Structure and Algorithms Part 1

Discover essential algorithmic principles, complexity analysis, and problem-solving techniques including sorting, graph theory, and optimization strategies for computational challenges.

• Coursera
• 1 day 8 hours 34 minutes
• Self-Paced
• Paid Course

Statistical Learning for Engineering Part 1

Explore supervised and unsupervised machine learning algorithms, from linear regression to SVMs, with hands-on Python implementation for real-world engineering applications.

• Coursera
• 1 day 11 hours 38 minutes
• Self-Paced
• Paid Course

Data Management for Analytics Part 2

Explore SQL fundamentals, NoSQL databases (MongoDB, Neo4j), and big data technologies to build essential data management skills for analytics and machine learning applications.

• Coursera
• 9 hours 40 minutes
• Self-Paced
• Paid Course

Machine Learning and Data Analytics Part 2

Explore advanced data mining techniques including clustering, neural networks, SVMs, and text mining with real-world applications across engineering sectors.

• Coursera
• 18 hours 25 minutes
• Self-Paced
• Paid Course