About this Course
Laique Merlin Djeutchouang
Your instructor here, Laique Merlin Djeutsch, is a Data and Research Scientist. As a science practitioner & enthusiast with a strong background in theoretical & applied mathematics, and statistics, Laique understood a little early how to leverage scientific computing and these skills to ask relevant business questions and turn data into insights. This allowed him to collaborate on a couple of Data Science & Machine Learning projects at the University College London, and the London Mathematical Laboratory. He taught at the African Institute for Mathematical Sciences (AIMS) for about 3 years.

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).
Course name:
Getting Started with Python for Data Science
There is no doubt that Python has become the most popular programming language for Data Science and competency in Python is a critical skill for students or anyone interested in this area. This course is a series of six modules introducing Python within the context of the closely related areas of mathematics, statistics, and Data Science.

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.
What you will learn:
1. Computing Platform

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.

3. Slack

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.

Course Modules

Module 1: Installing Anaconda & Setting up the Python Environments

➢ Jupyter
➢ Launching Jupyter
➢ Running Code in Jupyter
➢ Finding Function Help in Jupyter

Module 2: Introduction to Python

➢ Understanding Operators
➢ Variablesand DataTypes
➢ Conditional Statements
➢ Loop Constructs
➢ Functions

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
TZS 50,000.00
No prior programming experience is required, however, some exposure to statistics would be helpful, though not a necessity as relevant concepts will be covered in class.
Starts on:
30 Jun, 2021 06:00 PM +03:00
Ends on:
13 Jul, 2021 08:00 PM +03:00
Remaining seats:
Award upon completion: