Collaborating Authors



Those who learn how to make machines that exhibit intelligence today are tomorrow going to lead the next technological revolution, be part of the most cutting-edge companies and stand a chance to disrupt almost all industries through their skillsets.

Blockchain and Cyber Security Udemy


The high level of dependency on the internet and technology today has resulted in new revenue streams and business models for organizations, but with this arises new gaps and opportunities for hackers to exploit. Cybercriminals have become increasingly complex and are attempting to steal valuable data like financial data, health records, personal identifiable information (PII) and intellectual property, and are resorting to highly profitable strategies like disrupting the overall operations of a business via DDoS attacks, or monetizing data access via the utilization of advanced ransomware techniques. So, will blockchain technology be a cybersecurity help?

What is a Proof? Coursera


About this course: Mathematical thinking is crucial in all areas of computer science: algorithms, bioinformatics, computer graphics, data science, machine learning, etc. In this course, we will learn the most important tools used in discrete mathematics: induction, recursion, logic, invariants, examples, optimality. We will use these tools to answer typical programming questions like: How can we be certain a solution exists? Am I sure my program computes the optimal answer? Do each of these objects meet the given requirements?

Survey of Music Technology Coursera


About this course: How can we use computers to create expressive, compelling music? And how can we write computer software to help us create and organize sounds in new ways? This course provides a hands-on introduction to the field of music technology as both a creative musical practice and an interdisciplinary technical research pursuit. Students will be able to compose music in digital audio workstation software using both audio and symbolic representations; to write code to algorithmically generate music, analyze sound, and design sound; and to describe the essential theory and history behind these activities as well as their connection to cutting-edge computer music research. Through the exploration of topics such as acoustics, psychoacoustics, digital sound, digital signal processing, audio synthesis, spectral analysis, algorithmic composition, and music information retrieval, we will explore the deep relationships between art and science, between theory and practice, and between experimental and popular electronic music.