Data Analysis with Python
Data Analysis with Python – Certificate
IBM – Data Analysis with Python
About this Course
Learn how to analyze data using Python. This course will take you from the basics of Python to exploring many different types of data. You will learn how to prepare data for analysis, perform simple statistical analysis, create meaningful data visualizations, predict future trends from data, and more!
Topics covered:
- 1) Importing Datasets
- 2) Cleaning the Data
- 3) Data frame manipulation
- 4) Summarizing the Data
- 5) Building machine learning Regression models
- 6) Building data pipelines Data Analysis with Python will be delivered through lecture, lab, and assignments.
It includes following parts: Data Analysis libraries: will learn to use Pandas, Numpy and Scipy libraries to work with a sample dataset. We will introduce you to pandas, an open-source library, and we will use it to load, manipulate, analyze, and visualize cool datasets. Then we will introduce you to another open-source library, scikit-learn, and we will use some of its machine learning algorithms to build smart models and make cool predictions.
IBM
IBM offers a wide range of technology and consulting services; a broad portfolio of middleware for collaboration, predictive analytics, software development and systems management; and the world’s most advanced servers and supercomputers. Utilizing its business consulting, technology and R&D expertise, IBM helps clients become “smarter” as the planet becomes more digitally interconnected. IBM invests more than $6 billion a year in R&D, just completing its 21st year of patent leadership. IBM Research has received recognition beyond any commercial technology research organization and is home to 5 Nobel Laureates, 9 US National Medals of Technology, 5 US National Medals of Science, 6 Turing Awards, and 10 Inductees in US Inventors Hall of Fame.
Boris Kisov
Innovation, IT & Management
10+ years of initiating and delivering sustained results and effective change for companies across a wide range of industries including
innovation, enterprise software, digital marketing, start-ups, advertising technology, e-commerce and government.
