This tutorial will introduce the use of Python for statistical data analysis, using data stored as Pandas DataFrame objects. Much of the work involved in analyzing data resides in importing, cleaning and transf
Statistical Analysis Financial Analysis Data Visualization DataViz Random Variables Sampling Inference Linear Regression Coursera Plus Course Auditing Coursera The Hong Kong University of Science and Technology - HKUST Xuhu Wan Economics & Finance Business Hong Kong Intermediate 4 Weeks 1-4 Hour...
Who should take this course? It is designed for people who want to “move beyond Excel” and write more complex Python codes for data analysis and statistical testing. What we like What we don’t like Interactive exercises. Some content requires a subscription. Real-world examples. Lacks a ...
Check out the detailed breakdown of what’s inside the course Data Analysis using NumPy and Pandas 19 Lectures Introduction Preview 01:09 NumPy Introduction Preview 34:09 Python Numpy Array Preview 22:32 Indexing & Slicing - 1 19:29 Indexing & Slicing - 2 30:21 Statistical Functions...
This course will introduce you to time series analysis in Python. After learning what a time series is, you'll explore several time series models, ranging from autoregressive and moving average models to cointegration models. Along the way, you'll learn how to estimate, forecast, and simulate...
This is an introductory-level course in supervised learning, with a focus on regression and classification methods. The syllabus includes: linear and polynomial regression, logistic regression and linear discriminant analysis; cross-validation and the bootstrap, model selection and regularization methods (...
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 trend... ...
It offers additional functionality compared to NumPy, including scipy.stats for statistical analysis. pandas is a third-party library for numerical computing based on NumPy. It excels in handling labeled one-dimensional (1D) data with Series objects and two-dimensional (2D) data with DataFrame ...
The book consists of three parts: The first one presents data in the framework of probability theory, exploratory data analysis, and unsupervised learning. The second part on inferential data analysis covers linear and logistic regression and regularization. The last part studies machine learning with...
such as data cleaning, data manipulation, statistical analysis, and machine learning.By the end of this module, learners will have a good understanding of Python, be proficient in using Jupyter notebooks for data analysis, and comprehend how Python is used to address real-world data science chall...