Graph Theory Courses and Certifications

Business Analytics with Excel: Intermediate to Advanced

Master advanced Excel optimization techniques including linear, integer, network, and nonlinear programming with VBA macros for sophisticated business decision-making and multi-objective analysis.

• Coursera
• 12 hours 16 minutes
• Self-Paced
• Paid Course

Advanced Techniques in Data Visualization

Master advanced data visualization techniques to transform complex data into compelling visual stories using color theory, interactivity, network graphs, geospatial mapping, and text visualization methods.

• Coursera
• 1 day 4 hours 27 minutes
• Self-Paced
• Paid Course

Mastering Neural Networks and Model Regularization

Dive deep into neural networks, from perceptrons to CNNs. Build models from scratch, master regularization techniques, and apply PyTorch for image and audio processing tasks.

• Coursera
• 16 hours 3 minutes
• Self-Paced
• Paid Course

Network Visualization and Intervention

Explore data manipulation, visualization, and network dynamics. Master Relational Algebra, create impactful visualizations, and learn to influence social networks through strategic interventions.

• Coursera
• 12 hours 1 minute
• Self-Paced
• Paid Course

The Nuts and Bolts of Machine Learning

632 ratings at Coursera

Explore machine learning algorithms, from supervised to unsupervised techniques. Learn to apply models like Naive Bayes, decision trees, and K-means clustering to solve complex data problems and make predictions.

• Coursera
• 1 day 9 hours 53 minutes
• Self-Paced
• Paid Course

Optimization Methods in Asset Management

Explore optimization methods in asset management, covering Mean-Variance Analysis, CAPM, risk measurements, ETFs, and transaction costs modeling for practical portfolio construction and risk management.

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

Introduction to Machine Learning

2 ratings

Foundational understanding of machine learning models, hands-on implementation with PyTorch, and applications across industries from medical diagnostics to image recognition and text prediction.

• Coursera
• 1 day 1 hour 47 minutes
• Self-Paced
• Paid Course

Capstone: Analyzing (Social) Network Data

Analyze social networks to uncover influential members, sub-communities, and connections. Apply graph algorithms and data structures to explore real-world network data and showcase findings through a video presentation.

• Coursera
• 19 hours 49 minutes
• Self-Paced
• Paid Course

GenAI and LLMs on AWS

Deploy and manage LLMs on AWS using Amazon Bedrock. Learn to optimize performance, build secure pipelines, and comply with regulations through hands-on labs and real-world scenarios.

• Coursera
• 1 day 22 hours 11 minutes
• Self-Paced
• Paid Course

Machine Learning with Graphs

Master graph-based machine learning techniques including Graph Neural Networks, PageRank, knowledge graphs, and network analysis for modeling complex social, technological, and biological systems.

• YouTube
• 1 day 8 minutes
• Self-Paced
• Free Video

Machine Learning with Graphs

Master graph neural networks, node embeddings, and network analysis through Stanford's comprehensive exploration of machine learning algorithms for large-scale social and information networks.

• YouTube
• 22 hours 23 minutes
• Self-Paced
• Free Video

Introduction to Algorithms (SMA 5503)

3 ratings

This course teaches techniques for the design and analysis of efficient algorithms, emphasizing methods useful in practice.

• MIT OpenCourseWare
• 30 hours
• Self-Paced
• Free Video

Informatica Tutorial: Beginner to Expert Level

8850 ratings at Udemy

Become an expert in world's top Data Integration tool.

• Udemy
• 1 day 11 hours 11 minutes
• Self-Paced
• Paid Course

Java Data Structures and Algorithms Masterclass

7805 ratings at Udemy

100+ DSA Interview Questions for Cracking FAANG with Animated Examples for Deeper Understanding and Faster Learning

• Udemy
• 1 day 22 hours 39 minutes
• Self-Paced
• Paid Course

Designing Autonomous AI

Learn to design autonomous AI systems by breaking down complex tasks, setting goals, and incorporating expert knowledge into AI agents using various architecture patterns.

• Coursera
• 12 hours 37 minutes
• Self-Paced
• Paid Course