Data Analytics with Python
Session I : Introduction to Data Science with Python
In our first class, we will go over some Python fundamentals, which will cover syntax and built-in functions. We will move onto practicing For Loops and introducing the packages that will be covered over the course and how to install them.
Session II : Exploratory Data Analysis
We will start by introducing NumPy and Pandas and showcasing how to clean, manipulate, and analyze data. Students will practice on the Titanic dataset before moving onto web scraping techniques and extracting data from APIs.
Session III : Advanced NumPy and Pandas
We will begin by reviewing NumPy and Pandas before delving deeper into more advanced techniques to clean and munge data. Using Matplotlib and Seaborn packages, students will learn to visualize data and identify trends.
Session IV : Data Mining and Machine Learning With Hack Day
We will be introducing the Cross Industry Standard Process for Data Mining (CRISP-DM) and data mining with supervised learning and unsupervised learning. Afterwards, students will explore machine learning algorithms such as Regression (Linear, Multivariable, and Logistic), Naïve Bayes, Decision Trees, and Clustering.
One Machine learning project on Hack Day for example, Housing price, stock market prediction, web based recommendation system