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.
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.
Data Analysis with Python
Offered By
IBM
About this Course
4.6
2,569 ratings
Skills you will gain
Predictive ModellingPython ProgrammingData AnalysisData Visualization (DataViz)Model Selection
Syllabus - What you will learn from this course
Week
12 hours to complete
Importing Datasets
5 videos (Total 15 min), 6 quizzes
5 videos
Understanding the Data2m
Python Packages for Data Science2m
Importing and Exporting Data in Python4m
Getting Started Analyzing Data in Python4m
5 practice exercises
Understanding the Data4m
Python Packages for Data Science4m
Importing and Exporting Data in Python4m
Getting Started Analyzing Data in Python4m
Importing Datasets16m
Week
22 hours to complete
Data Wrangling
6 videos (Total 19 min), 6 quizzes
6 videos
Dealing with Missing Values in Python5m
Data Formatting in Python3m
Data Normalization in Python3m
Binning in Python1m
Turning categorical variables into quantitative variables in Python2m
5 practice exercises
Dealing with Missing Values in Python6m
Data Formatting in Python4m
Data Normalization in Python4m
Turning categorical variables into quantitative variables in Python4m
Data Wrangling12m
Week
32 hours to complete
Exploratory Data Analysis
6 videos (Total 18 min), 6 quizzes
6 videos
Descriptive Statistics4m
GroupBy in Python3m
Correlation2m
Correlation - Statistics2m
Analysis of Variance ANOVA3m
5 practice exercises
Descriptive Statistics4m
GroupBy in Python4m
Correlation4m
Correlation - Statistics4m
Exploratory Data Analysis14m
Week
42 hours to complete
Model Development
6 videos (Total 26 min), 6 quizzes
6 videos
Linear Regression and Multiple Linear Regression6m
Model Evaluation using Visualization4m
Polynomial Regression and Pipelines4m
Measures for In-Sample Evaluation3m
Prediction and Decision Making5m
5 practice exercises
Linear Regression and Multiple Linear Regression4m
Model Evaluation using Visualization4m
Polynomial Regression and Pipelines4m
Measures for In-Sample Evaluation4m
Model Development15m
4.6
346 Reviews46%
started a new career after completing these courses
44%
got a tangible career benefit from this course
Top Reviews
I have been looking for a very non-complicated course on data analysis and I hit the Jackport with this course! Very simplified and explanatory. You should definitely take the course
Really this course shows the full path to master the Data Analysis with Python. This path is short, helpful, and rich information their. thank you at all and thank you Coursera
Instructor
Joseph Santarcangelo
Ph.D., Data Scientist at IBMIBM Developer Skills Network
About 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.
Frequently Asked Questions
When will I have access to the lectures and assignments?
Once you enroll for a Certificate, you’ll have access to all videos, quizzes, and programming assignments (if applicable). Peer review assignments can only be submitted and reviewed once your session has begun. If you choose to explore the course without purchasing, you may not be able to access certain assignments.
What will I get if I subscribe to this Certificate?
When you enroll in the course, you get access to all of the courses in the Certificate, and you earn a certificate when you complete the work. Your electronic Certificate will be added to your Accomplishments page - from there, you can print your Certificate or add it to your LinkedIn profile. If you only want to read and view the course content, you can audit the course for free.
What is the refund policy?
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