Table of Contents
This is a collection of both my active and archived course notes. They are mostly for my personal use. However, I open-source them with the hope that someone may find them useful as well, this originally was created by schlomok.
I also maintain a list of intended courses.
The structure of this repository utilizes in the following pattern:
notebook/{subject}/{program}/{course}/{...}, where {...} is reflected by
the structure of that specific course. Often, this structure is based on weeks.
Sometimes, courses are not part of programs, however. In this case, they follow
notebook/{subject}/{course}/{...}.
| Subject | Course | Program | School | Platform | Notes | Dates |
|---|---|---|---|---|---|---|
| scholarship | Advanced Data Analysis | *Apply inferential statistics and probability to real-world scenarios using Python *Create and analyze the results of hypothesis testing and A/B test results *Build regression models and visualizations using different design elements to explore data and communicate insights * Gain exposure to the freelancing landscapes and learn to write winning proposals and learn bidding tactics to win key projects | udacity | udacity | Notes | July 15 2020 |
| scholarship preparation | English, IQ, Technical, Soft skills and Fundamentals | join ITI | ministry of communications and information technology egypt | Self Study | Notes | July 1 2020 |
| DataScience | Exploratory Data Analysis | This course covers the essential exploratory techniques for summarizing data. These techniques are typically applied before formal modeling commences and can help inform the development of more complex statistical models. Exploratory techniques are also important for eliminating or sharpening potential hypotheses about the world that can be addressed by the data. We will cover in detail the plotting systems in R as well as some of the basic principles of constructing data graphics. We will also cover some of the common multivariate statistical techniques used to visualize high-dimensional data. | Johns Hopkins University | coursera | Notes | June 17 2020 |
| Programing | Using Python to Access Web Data | This course will show how one can treat the Internet as a source of data. We will scrape, parse, and read web data as well as access data using web APIs. We will work with HTML, XML, and JSON data formats in Python. This course will cover Chapters 11-13 of the textbook “Python for Everybody”. To succeed in this course, you should be familiar with the material covered in Chapters 1-10 of the textbook and the first two courses in this specialization. These topics include variables and expressions, conditional execution (loops, branching, and try/except), functions, Python data structures (strings, lists, dictionaries, and tuples), and manipulating files. This course covers Python 3. | University of Michigan | coursera | Notes | July 1 2020 |
| Data Science | Applied Data Science Capstone | This capstone project course will give you a taste of what data scientists go through in real life when working with data. | IBM | coursera | Notes | ** |
| Math | Mathematical Thinking in Computer Science | algorithms, bioinformatics, computer graphics, data science, machine learning, etc, most important tools used in discrete mathematics | University of California San Diego & National Research University Higher School of Economics | coursera | In external notebook | July 1 |
| Algorithms | Algorithmic Toolbox | covers basic algorithmic techniques and ideas for computational problems | University of California San Diego & National Research University Higher School of Economics | coursera | In external notebook | July 1 |
| Notes | ** |
| Subject | Course | Program | School | Platform | Notes | Dates |
|---|---|---|---|---|---|---|
| Subject | Course | Program | School | coursera | Notes | Dates |
| Subject | Course | Program | School | coursera | Notes | Dates |
| Subject | Course | Program | School | coursera | Notes | Dates |
| Subject | Course | Program | School | coursera | Notes | Dates |
| Subject | Course | Program | School | coursera | Notes | Dates |
| Subject | Course | Program | School | coursera | Notes | Dates |
| Subject | Course | Program | School | coursera | Notes | Dates |
| Subject | Course | Program | School | coursera | Notes | Dates |
| Subject | Course | Program | School | coursera | Notes | Dates |
| Subject | Course | Program | School | coursera | Notes | Dates |
| Subject | Course | Program | School | coursera | Notes | Dates |