Last updated on April 7, 2020
Since 2014, I have systematically prepared a series of documents called “Guided Tours,” which consist of carefully curated material and cutting-edge resources, organized as a sequence of steps that provide a road map to guide students through concepts and technologies, allowing them to learn (more) about a specific language, software package or set of technologies with a systematic and confidence-building approach.
My Guided Tours contain numerous free resources, including tools, videos, and interactive tutorials. They are respectful of students’ learning style, allow self-paced learning, and include optional steps for those who want to go above and beyond.
Examples of Guided Tours (some of which are available in my Resources page) include:
- A Guided Tour to JavaScript: guides students through the intricacies of the JavaScript programming language and its use in client-side development of web pages and web-based apps.
- A Guided Tour to PHP: helps students master the PHP programming language and the MySQL database management system, which are among the most popular environments for server-side development of web pages and web-based apps.
- A Guided Tour to the MEAN Stack: covers the four key technologies behind the MEAN acronym (MongoDB, Express.js, Angular, and Node.js) which, together, represent one of the most popular stacks for the development of advanced web-based apps.
- A Guided Tour to Machine Learning Using MATLAB: guides students through the basics of Machine Learning using the MATLAB scientific package and some of its toolboxes and apps, particularly the Classification Learner App.
- A Guided Tour to Deep Learning Using MATLAB: guides students through the basics of Deep Learning using MATLAB and some of its toolboxes and apps.
- A Guided Tour to Machine Learning Using Python: guides students through the basics of Machine Learning using the Python scientific stack (NumPy, Scikit-Learn, Matplotlib, Pandas), Keras, and TensorFlow.
- A Guided Tour to Data Science Using Python: guides students through the basics of Data Science and statistical analysis using the Python scientific stack (NumPy, Scikit-Learn, Matplotlib, Pandas), and statistics packages (e.g., thinkstats2).
- A Guided Tour to Deep Learning Using R: guides students through the basics of Deep Learning using R, RStudio, Keras, and TensorFlow.
Featured image: photo by Daniil Silantev on Unsplash