Data Science With Python
The Python Data Science course teaches you to master the concepts of Python programming. Through this Python for Data Science training, you will gain knowledge in data analysis, machine learning, data visualization, web scraping, & natural language processing. Upon course completion, you will master the essential tools of Data Science with Python.
This self-paced E learning course is done in partnership with SimpliLearn. It consists of a few videos that will take approximately 8 hours in total to finish the course. Upon successful completion of the Data Science with Python online course, you will receive a completion certificate from SimpliLearn and Aventis that will be able to enhance your portfolio.
The demand for Data Science professionals has surged, making this course well-suited for participants at all levels of experience. This Python for Data Science training is beneficial for analytics professionals willing to work with Python, Software, and IT professionals interested in the field of analytics, and anyone with a genuine interest in Data Science.
To best understand the Python Data Science course, it is recommended that you begin with the courses including, Introduction to Data Science in Python, Math Refresher, Data Science in Real Life, and Statistics Essentials for Data Science. These courses are offered as free companions with this program.
Data Science with Python
Lesson 00 – Course Overview
Lesson 01 – Data Science Overview
Lesson 02 – Data Analytics Overview
Lesson 03 – Statistical Analysis and Business Applications
Lesson 04 – Python Environment Setup and Essentials
Lesson 05 – Mathematical Computing with Python (NumPy)
Lesson 06 – Scientific computing with Python (Scipy)
Lesson 07 – Data Manipulation with Pandas
Lesson 08 – Machine Learning with Scikit–Learn
Lesson 09 – Natural Language Processing with Scikit Learn
Lesson 10 – Data Visualization in Python using matplotlib
Lesson 11 – Web Scraping with BeautifulSoup
Lesson 12 – Python integration with Hadoop MapReduce and Spark
Practice Projects: IBM HR Analytics Employee Attrition Modeling