Soil Science Courses

Data Science Fundamentals Part 2: Unit 3

Master statistical modeling and machine learning with Python using real Airbnb data, covering probability, regression, model evaluation, and Scikit-learn implementation.

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

Education on climate change: water and soil

Explora la relación entre agua, cambio climático y adaptación de organismos, abordando agricultura y soberanía alimentaria. Incluye juegos en línea para aplicar conocimientos y propone un plan de mitigación escolar.

• Coursera
• 7 hours 2 minutes
• Self-Paced
• Paid Course

Coursera

Essential Causal Inference Techniques for Data Science

Learn key causal inference techniques for data science, including controlled regression, regression discontinuity, difference-in-difference, and instrumental variables, with practical applications in R.

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

Packt

Engaged: Behavioral Science for Digital Product Design

Discover how to apply behavioral science principles to create digital products that drive lasting user engagement and meaningful behavior change through psychology-backed design strategies.

• Coursera
• 17 hours 56 minutes
• Self-Paced
• Paid Course

Packt

Foundations of ML & Python for Data Science

Gain insights into machine learning fundamentals and Python programming for data science, covering statistical techniques, key libraries like NumPy and Pandas, and practical applications across industries.

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

CertNexus

Finalize a Data Science Project

Learn to present data science project results to stakeholders, build a web app for model demonstration, and automate model training and deployment pipelines. Ideal for experienced professionals in the CDSP program.

• Coursera
• 12 hours 22 minutes
• Self-Paced
• Paid Course

Machine Learning Models in Science

Explore machine learning techniques for scientific problems, from data preprocessing to advanced algorithms like neural networks, using medical and astronomical datasets.

• Coursera
• 11 hours 50 minutes
• Self-Paced
• Paid Course

Linear Algebra for Machine Learning and Data Science

Master linear algebra fundamentals for machine learning, including vectors, matrices, transformations, and eigenvectors. Apply concepts using Python in hands-on exercises to enhance your data science skills.

• Coursera
• 1 day 10 hours 8 minutes
• Self-Paced
• Paid Course

Fred Hutchinson Cancer Center

Making Science Reproducible - A Capstone Course

Master reproducible research workflows through hands-on Docker containerization, GitHub secrets management, and automated testing with GitHub Actions for scientific computing.

• Coursera
• 7 hours 46 minutes
• Self-Paced
• Paid Course

Genentech

Making Data Science Work for Clinical Reporting

Explore data science principles for efficient clinical reporting, focusing on transparency, DevOps practices, version control, code reusability, and risk management in clinical trials.

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

Packt

Learn the Art and Science of PCB Design with Eagle

Master PCB design with Eagle software through hands-on projects, from basic schematics to advanced double-sided boards, custom components, and manufacturing-ready outputs for professional electronic circuits.

• Coursera
• 8 hours 11 minutes
• Self-Paced
• Paid Course

Packt

Julia Programming for Data Science and Machine Learning

Master Julia v1.8 for data science and machine learning, covering type systems, metaprogramming, interoperability, visualization, and scientific computing with hands-on, real-world applications.

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

Introduction to R Programming for Data Science

Learn R programming essentials for data science: data types, manipulation techniques, and fundamental tasks. Gain practical skills through hands-on exercises using RStudio and Jupyter notebooks for data analysis.

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

Packt

NumPy, Matplotlib & Pandas – Data Science Prerequisites

Master essential Python data science libraries: NumPy for numerical computing, Matplotlib for visualization, and Pandas for data manipulation, plus introductions to SciPy and machine learning fundamentals.

• Coursera
• 7 hours 11 minutes
• Self-Paced
• Paid Course

Packt

Mastering Python for Data Science

Unlock Python's power for data analysis, visualization, and machine learning through hands-on projects and real-world case studies spanning statistics to big data processing.

• Coursera
• 17 hours 46 minutes
• Self-Paced
• Paid Course