This course will help you to learn the concepts and tools to utilize in a data science project.
In this heavy demo-based course, we shall teach you a practical approach to develop an end-to-end data science project cycle right from extracting data from different types of sources to exposing your machine learning model that can be consumed in a real-world data solution. We will teach an industry standard approach on data science project using Python.
The students will learn to use various standard libraries in the Python ecosystem such as Pandas, NumPy, Matplotlib, Scikit-Learn, Pickle, Flask to tackle different stages of a data science project such as extracting data, cleaning and processing data, building and evaluating machine learning model.
Finally, the students will learn how to expose the machine learning model as APIs. After the completion of the course, the students will have a solid foundation to handle any data science project and have the knowledge to apply various Python libraries to create a data science solution.
Following topics are included in this course:
- Python for Data Science - Introduction
- Setting up Working Environment
- Extracting Data from multiple sources
- Data Cleansing and pre processing
- Exploring and Processing Data
- Building and Evaluating Predictive Models
This course is suitable for those who already have basic knowledge of Python programming. Our Python Programming for Beginners Training Courses cover all of the prerequisites.