Applied Python: Web Dev, Machine Learning & Cryptography

Develop practical Python web development skills as you learn to create, connect, parse, publish, and deploy applications. Designed for learners with foundational Python knowledge, this course provides a structured path through GUI development, networking, web data processing, asynchronous programming, and deployment. You’ll build interactive applications with wxPython, apply layouts and event handling, enhance GUI-based text editors, and add database support for persistent data. You’ll use socket, urllib, and file modules to create network-aware applications, transfer data, and support multiple client connections. With asyncio and the Twisted framework, you’ll develop non-blocking, event-driven applications using concurrency models, Deferred objects, and reactor loops. You’ll also clean and parse HTML with Tidy and Python parsing libraries, extract web data with Beautiful Soup, and create server-side applications with CGI scripts, HTTP headers, and web forms. Finally, you’ll configure Apache for CGI, deploy dynamic content with Python Server Pages and Webware Publisher, generate RSS feeds, and enable remote communication through XML-RPC. What makes this course distinctive is its hands-on progression from desktop interfaces and networking to web publishing and Python application deployment. Enroll to build practical, connected Python applications and confidently publish Python-powered services on the web.

Build practical Python web development skills across the application lifecycle—from preparing web content to testing, integration, and distribution. Designed for learners who want to strengthen their Python skills, this course provides hands-on experience with server-side scripting and cross-platform development. You’ll clean malformed HTML with Tidy, parse structured web content with Python libraries and Beautiful Soup, and create dynamic CGI applications. You’ll diagnose CGI errors, configure Apache for script execution, generate server-side HTML with Python Server Pages, map URLs with Publisher, and produce RSS content. You’ll also implement XML-RPC communication, validate code with doctest and unittest, and use profiling tools to assess application performance. Finally, you’ll explore Python integration with Java and .NET through Jython and IronPython, extend Python with C, examine memory management through reference counting, and package modules for distribution with distutils. By the end, you’ll be able to prepare and serve web content, build and debug server-side applications, test reliability, analyze performance, integrate Python across runtime environments, and package applications for distribution. Its distinctive end-to-end focus connects web parsing, server configuration, testing, optimization, interfacing, and packaging in one structured learning path. Enroll to develop practical skills for building dependable Python-based web systems.

Build practical skills in linear regression, Python, and supervised machine learning through a structured, project-driven course. Designed for beginners and aspiring data professionals, this course guides you through the complete regression workflow—from identifying a machine learning use case and setting up essential Python libraries to exploring data, training a model, and evaluating its predictions. You’ll use exploratory data analysis (EDA) and graphical techniques to interpret univariate and bivariate distributions, examine relationships between independent and dependent variables, and identify outliers and patterns in variable spread. You’ll then prepare data, construct a simple linear regression model, generate predictions, compare predicted and real-world values, and apply evaluation metrics to assess model accuracy and effectiveness. What makes this course distinctive is its focused progression from data understanding to model validation, supported by practical demonstrations and structured assessments aligned with Bloom’s Taxonomy. By the end, you’ll be able to analyze regression data, build and evaluate a linear regression model in Python, and interpret performance results with confidence. Enroll to establish a practical foundation in Python-based regression analysis and predictive modeling.

Learn how to apply and analyze cryptographic systems using Python through practical, case-based implementation. This course guides you from foundational cryptography concepts and simple reverse and Caesar ciphers to brute force attacks, transposition ciphers, and classical multiplicative and affine encryption. You’ll develop Python programs for encryption and decryption, automate English detection, apply modular arithmetic, generate cipher keys, and examine how attackers exploit patterns and weaknesses. You’ll also implement substitution, Vernam, and Vigenère ciphers while evaluating their cryptographic strength and susceptibility to cryptanalysis. The course then introduces modern cryptography, including Base64 encoding, hashing algorithms, cryptographic libraries, and RSA public-key cryptography. You’ll distinguish encoding from encryption, apply hashing for data security, and construct and validate RSA key pairs for secure message exchange. Designed for learners interested in Python programming, cryptography, and secure communication, this course uniquely connects cryptographic theory with hands-on case studies. By the end, you’ll be able to build encryption and decryption tools, analyze cipher vulnerabilities, compare classical and modern techniques, and implement cryptographic methods in Python. Enroll to develop practical skills in designing, testing, and evaluating secure communication systems.