This course will not only help you to understand various data science related concepts, but also help you to implement the concepts in an industry standard approach by utilizing Python and related libraries. First, you will be introduced to the various stages of a typical data science project cycle and a standardized project template to work on any data science project. Then, you 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 you'll dive into exposing the machine learning model as APIs. You will also go through a case study that will encompass the whole course to learn end-to-end execution of a data science project.
By the end of this course, you will have a solid foundation to handle any data science project and have the knowledge to apply various Python libraries to create your own data science solutions.
Fueled by big data and AI, demand for data science skills is growing exponentially, according to job sites with an average increase of 29% year over year. The supply of skilled applicants, however, is growing at a slower pace – searches by job seekers skilled in data science grow on average by 14% year over year.
Skills you will gain
A minimum of 2 hours a week. All software used in this course is either available for free or as a demo version. Python Crash Course available upon registration.
What you will learn
Setting up Working Environment
Exploring and Processing Data
Building and Evaluating Predictive Models
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Tickets for Applied Data Science with Python Track can be booked here.
|Ticket Information||Ticket Price|
|Standard Registration||USD 85|
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