In this Specialization, developed by Rice University’s esteemed Computer Science and Data Science faculty, I gained essential programming skills in Python 3.
It comprises four courses, each concluding with a practical project reinforcing Python scripting abilities.
I learned how to tackle core scripting challenges, such as processing dates and comparing similar files. As the specialization progressed, I worked with real-world data, including sports analytics and visualizing data.
Key projects involved analyzing historical baseball data and culminated with a significant project where I imported economic data from the World Bank, processed it, and visualized it on a world map.
I achieved high grades throughout the courses, showcasing my understanding of Python programming, data analysis, and visualization.
Grade received: 98%
The specialization consists of four courses:
1- Python Programming Essentials
In this course, I was introduced to the fundamentals of Python programming, covering essential elements such as expressions, variables, functions, logic, and conditionals.
This foundational knowledge is crucial for constructing basic Python programs and thinking like a programmer.
The course also emphasized the use of Python modules, which provide access to the extensive functionalities within the Python language.
By the end of the course, I gained the skills to write short Python programs that accomplish practical tasks, laying the groundwork for more complex programming.
Utilizing the CodeSkulptor development environment, designed for beginners and accessible through modern web browsers, I was able to start writing and running programs without needing any installations.
This course served as the first step in a specialization, preparing me for advanced Python programming in subsequent courses.
Grade Achieved: 95.71%
2- Python Data Representations
In this course, I continued my journey in Python programming, building upon the foundational skills acquired in the **Python Programming Essentials** course. This course focused on various data representations, including strings, lists, and tuples, which are essential for all Python programs.
I learned how to access files, enabling me to store and retrieve data within my programs.
By the end of the course, I gained the ability to write Python programs that manipulate data stored in files, significantly enhancing my programming expertise and allowing me to create a broader range of scripts.
The course used Python 3, emphasizing its importance for future programming, and introduced basic desktop development environments, facilitating a smooth transition from online coding platforms to running Python programs directly on my computer.
Grade received: 99.17%
3- Python Data Analysis
In this course, I advanced my Python programming skills by building upon the knowledge gained in the previous courses, Python Programming Essentials, and Python Data Representations. This course focused on reading, storing, and processing tabular data, essential tasks in data analysis.
I learned about CSV files, a widely used plain text format that facilitates the exchange of tabular data between various programs, and how to read and write these files using Python.
By the end of the course, I became proficient in working with tabular data in Python, which further expanded my programming expertise and enabled me to create a broader range of scripts.
Grade received: 97.85%
4- Python Data Visualization
In this course, the final course in the specialization, I built upon the foundational knowledge gained from Python Programming Essentials, Python Data Representations, and Python Data Analysis. The course focused on installing external packages in Python, acquiring data from web sources, and cleaning, processing, analyzing, and visualizing that data.
By the end of the course, I became proficient in installing Python packages, analyzing existing datasets, and creating visual representations of that data.
This course rounded out my education as a Python scripter, equipping me with the skills to locate, install, and utilize third-party Python packages effectively.
Grade received: 100%