關於此課程：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 analyses, create meaningful data visualizations, predict future trends from data, and more! Topics covered: 1) Importing Data sets 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. If you choose to take this course and earn the Coursera course certificate, you will also earn an IBM digital badge. LIMITED TIME OFFER: Subscription is only $39 USD per month for access to graded materials and a certificate.
此課程適用人群：this course is geared for anyone with basic programming skills and has a knowledge of general mathematics
教學方： Joseph Santarcangelo, Ph.D., Data Scientist at IBM
IBM Developer Skills Network
| 基本信息 | |
| 級別 | 初級 |
| 承諾學習時間 | This course requires approximately two hours a week for six weeks |
| 語言 | English |
| 如何通過 | 通過所有計分作業以完成課程。 |
| 用戶評分 |
- 視頻: Understanding the Data
- 視頻: Python Packages for Data Science
- 視頻: Importing and Exporting Data in Python
- 視頻: Getting Started Analyzing Data in Python
- Elemento LTI: Lab 1:Importing Datasets
- 視頻: Dealing with Missing Values in Python
- 視頻: Data Formatting in Python
- 視頻: Data Normalization in Python
- 視頻: Binning in Python
- 視頻: Turning categorical variables into quantitative variables in Python
- Elemento LTI: Data Wrangling
- 視頻: Descriptive Statistics
- 視頻: GroupBy in Python
- 視頻: Analysis of Variance ANOVA
- 視頻: Correlation
- 視頻: Correlation - Statistics
- Elemento LTI: Exploratory Data Analysis
- 視頻: Linear Regression and Multiple Linear Regression
- 視頻: Model Evaluation using Visualization
- 視頻: Polynomial Regression and Pipelines
- 視頻: Measures for In-Sample Evaluation
- 視頻: Prediction and Decision Making
- Elemento LTI: Model Development
- 視頻: Overfitting, Underfitting and Model Selection
- 視頻: Ridge Regression
- 視頻: Grid Search
- Elemento LTI: Model Evaluation and Refinement
Cada curso es como un libro de texto interactivo, con videos pregrabados, cuestionarios y proyectos.
Conéctate con miles de estudiantes y debate ideas y materiales del curso, y obtén ayuda para dominar los conceptos.
Obtén reconocimiento oficial por tu trabajo y comparte tu éxito con amigos, compañeros y empleadores.
| 購買課程 | |
|---|---|
| 訪問課程材料 | 可用 |
| 訪問評分的材料 | 可用 |
| 收到最終成績 | 可用 |
| 獲得可共享的課程證書 | 可用 |
Very good labs and videos. Thank you!
This is very condense course. However the quizzes after every chapter are very timely, and one at the end of the week for entire week, helped a lot. The labs seems very real world, downloaded some notebook am sure will be using them in real world later on.
Amazing course. Best yet
J
s实际的案例不够多