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Overview
Learn how to analyze data using Python. This Analyzing Data with Python course at IBMx 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!
What you will learn
You will learn how to:
Import data sets
Clean and prepare data for analysis
Manipulate pandas DataFrame
Summarize data
Build machine learning models using scikit-learn
Build data pipelines
Data Analysis with Python is delivered through lecture, hands-on labs, and assignment.
It includes following parts:
Data Analysis libraries: will learn to use Pandas DataFrames, Numpy multi-dimentional arrays, and SciPy libraries to work with a various datasets. 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.
Get more details
Visit official programme websiteProgramme Structure
Courses include:
Module 1 - Importing Datasets
- Learning Objectives
- Understanding the Domain
- Understanding the Dataset
- Python package for data science
- Importing and Exporting Data in Python
- Basic Insights from Datasets
Module 2 - Cleaning and Preparing the Data
- Identify and Handle Missing Values
- Data Formatting
- Data Normalization Sets
- Binning
- Indicator variables
Module 3 - Summarizing the Data Frame
- Descriptive Statistics
- Basic of Grouping
- ANOVA
- Correlation
- More on Correlation
Module 4 - Model Development
- Simple and Multiple Linear Regression
- Model Evaluation Using Visualization
- Polynomial Regression and Pipelines
- R-squared and MSE for In-Sample Evaluation
- Prediction and Decision Making
Module 5 - Model Evaluation
- Model Evaluation
- Over-fitting, Under-fitting and Model Selection
- Ridge Regression
- Grid Search
- Model Refinement
Check out the full curriculum
Visit official programme websiteKey information
Duration
- Part-time
- 35 days
- 2 hrs/week
Start dates & application deadlines
You can apply for and start this programme anytime.
Language
English
Delivered
Online
- Self-paced
Disciplines
Computer Sciences Data Science & Big Data Machine Learning View 300 other Short Courses in Machine Learning in United StatesExplore more key information
Visit official programme websiteAcademic requirements
We are not aware of any specific GRE, GMAT or GPA grading score requirements for this programme.
English requirements
We are not aware of any English requirements for this programme.
Other requirements
General requirements
Prerequisites
- Some Python Experience
Make sure you meet all requirements
Visit official programme websiteTuition Fee
To always see correct tuition fees
-
International
FreeTuition FeeBased on the tuition of 0 USD for the full programme during 35 days. -
National
FreeTuition FeeBased on the tuition of 0 USD for the full programme during 35 days.
- Add a Verified Certificate for $99 USD
- Limited access:free
Funding
Studyportals Tip: Students can search online for independent or external scholarships that can help fund their studies. Check the scholarships to see whether you are eligible to apply. Many scholarships are either merit-based or needs-based.
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