Currently, while pursuing his doctoral studies with the Council of Scientific and Industrial Research (CSIR) through the Southern Ocean Carbon and Climate Observatory (SOCCO), and the Marine Research Institute at the University of Cape Town, Laique also works as a Data Science Consultant at one of the most promising South African startups in Artificial Intelligence (AI).
At the end of the course, learners will have a solid understanding of Python programming basics and have been exposed to the entire Data Science workflow, starting from interacting datasets locally stored in their system and retrieve data, data wrangling, reshaping, summarizing, analyzing and ultimately reporting results. The course will introduce and make use of popular Python packages such as Numpy and Pandas, and use Jupyter notebook framework for interactive programming.
In this course we will make use of the Anaconda Distribution Platform which includes only Python but also comes with Jupyter notebooks, and Spyder IDE, together with the majority of Python libraries needed for the class. Though the first module of the course includes setting up all the computing materials necessary for the class, installing the software in your system before the first is an extremely good idea!
2. Data and Sources
The course will use real-life datasets from a variety of disciplines including healthcare, finance, marketing and internet sources.
There will be an online discussion forum allocated to this course to extend discussion on relevant concepts covered in class, and also topics related to the course. Though the discussions will be monitored by a team of experienced tutors, we strongly encourage learners to ask questions and get involved in answering questions from their fellow classmates. We believe that such interactions are crucial in boosting your learning experience. We will use Slack as the discussion forum environment.
Module 1: Installing Anaconda & Setting up the Python Environments
➢ Launching Jupyter
➢ Running Code in Jupyter
➢ Finding Function Help in Jupyter
Module 2: Introduction to Python
➢ Understanding Operators
➢ Variablesand DataTypes
➢ Conditional Statements
➢ Loop Constructs
Module 3: Fundamentals for Data Manipulation with Python
➢ Data Structures
➢ Lists and Dictionaries
➢ Understanding Standard Libraries in Python
Module 4: Reading Data Files (.csv & .txt) in Python
➢ Introduction to Pandas Library
➢ BasicData Processing with Pandas
Module 5: More Data Processing with Pandas
➢ DataFrames and Basic Operations with DataFrames
➢ Indexing a DataFrame
➢ DataWrangling, Reshaping, Summarizing with Pandas
Module 6: Visualization using Matplotlib and Seaborn
➢ Introduction to Matplotlib and Seaborn libraries
➢ Data Visualization using Matplotlib and Seaborn