Advance Your ML & DL Skills with PRStats — R and Python Paths Available Advance Your Machine Learning & Deep Learning Skills with PRStats with our comprehensive selection on ML and DL courses from beginner to advanced delivered live and on demand allowing you to work at your own pace.
Whether you prefer *R* or *Python*, the comprehensive course portfolio from PRStats delivers practical, hands-on training in machine learning and deep learning — from foundational methods to advanced applications. Choose the language and learning path that suits your background and research or project needs. What’s on OfferIn *R* - *Deep Learning using R (DLUR01)* — Dive into neural networks, build MLPs, CNNs, even transformer-style language models, all within the R ecosystem. https://prstats.org/course/deep-learning-using-r-dlur01/ <https://prstats.org/course/deep-learning-using-r-dlur01/?utm_source=chatgpt.com> - *A Comprehensive Introduction to Machine Learning (CIMLPR)* — A broad, robust overview of ML methods and workflows, ideal if you're starting out or want a coherent foundation. https://prstats.org/course/a-comprehensive-introduction-to-machine-learning-cimlpr/ - *Introduction to Machine Learning (IMLRPR)* — A lighter-entry ML course for newcomers, covering essential algorithms and data preparation in R. https://prstats.org/course/introduction-to-machine-learning-imlrpr/ - *Machine Learning — Intermediate to Advanced (MLIAPR)* — For those who already know the basics and want to extend into more complex models, tuning, and real-world data workflows. https://prstats.org/course/machine-learning-intermediate-to-advanced-mliapr/ In *Python* - *Deep Learning using Python (DLUP01)* — Learn to build, train and evaluate deep learning models using Python’s rich ML libraries and frameworks. https://prstats.org/course/deep-learning-using-python-dlup01/ - *Machine Learning using Python (MLUPPR)* — A practical, Python-based course in classical machine learning: data preprocessing, supervised/unsupervised methods, model evaluation, etc. https://prstats.org/course/machine-learning-using-python-mluppr/ - *Machine Vision using Python (MVUPPR)* — Specialised for image data, this course covers computer vision techniques, convolutional networks, and image-based ML pipelines. https://prstats.org/course/machine-vision-using-python-mvuppr/ Why This Suite Is Valuable - *Flexibility* — Choose to learn in R or Python depending on your comfort and project context. - *Comprehensive coverage* — From basic ML through advanced deep-learning and domain-specific applications (like computer vision), you can build a full skill set. - *Hands-on and practical* — Courses emphasise applying methods to real data, not just theory; suitable for research, conservation, bioinformatics, environmental data, vision tasks, and more. - *Progressive learning paths* — Start with basics if new, or pick up advanced courses if you already have foundational skills. Who Should Consider Enrolling - Researchers, analysts, data scientists, or students working with ecological, biological, environmental, or other real-world datasets. - Anyone needing to apply predictive models, image analysis, spatial data, or deep learning in R or Python. - Professionals wanting to boost their data-science toolkit for applied projects, publications, or industry tasks. Email [email protected] with any questions -- Oliver Hooker PhD. PR stats [[alternative HTML version deleted]] _______________________________________________ R-sig-ecology mailing list [email protected] https://stat.ethz.ch/mailman/listinfo/r-sig-ecology
