What you’ll learn

• Foundations of Data Science & Machine Learning
• Beginner Python Programming Skills
• Core Statistical Understanding
• Data Handling with Pandas & Visualization with Matplotlib
• Predictive Modeling Basics
• Introduction to ML Algorithms

Course description

Introduction to Data Science Using Python course provides a perfect way to enter the fascinating world of data when it comes to high school and college students. This newcomer course lasts more than 8 weeks and gives a basic idea of the areas related to data science and machine learning, but all of them are presented through the prism of Python programming. Members will start with simple data types, control structures, and functions in Python using Spyder. Then they transition into the more complicated data types like arrays, dictionaries, and dataframes. With the development of students, they receive an idea of the statistical methods that support data science, descriptive, and inferential statistics.

Data visualization skills with Matplotlib and Seaborn are also important in the course, which allows the learner to explore and communicate the findings on the actual datasets. Every module is strengthened by topics such as data preprocessing, exploratory analysis, and practical exercises. The students will subsequently learn the foundations of machine learning, predictive modelling using regressions, classification, and clustering, such as logistic regression, k-NN, and K-means. Every week will entail guided code labs and assignments. The concepts are related and practical as case studies (i.e., an example of predicting the price of cars). Having highly knowledgeable faculty and a very supportive environment, students will pass through this course with a good knowledge of data science and have the assurance to study further topics at a higher level.