Description
The Data Literacy Training is a 4-day program, delivered live online or in person, that covers understanding, interpreting and using data through Python-based hands-on work. The curriculum runs from core data science concepts to data preprocessing, exploratory analysis and visualization.
The program includes the CRISP-DM methodology; Pandas, NumPy, Matplotlib and Seaborn; loading data from files; basic statistics; and working with missing and duplicate data. Analysis exercises on ready-made data sets and report creation tools are also part of the current scope.
Outline
Data Science Basic Concepts
- What Is Data?
- What Is Data Analysis? What Can Be Done with Data Analysis?
- What Is Data Science?
- What Are the Elements of Data Science?
- How Do the Stages of Extracting Useful Information from Data Work? (Data Analytics)
- Areas of Use of Data Science
Data Literacy
- What Is Data Literacy?
- Basic Concepts of Data Literacy
- Defining Data
- Organizing and Reducing Data
- Presenting Data
- Data Analysis and Evaluation
How Is Data Science Applied in the Business Process Cycle?
- CRISP-DM Methodology
- Business Understanding
Tools Used for Application Development in Data Science
- Pandas (Data Manipulation)
- NumPy (Algebraic Operations)
- Matplotlib and Seaborn (Data Visualization)
Data Literacy Applications with Python
- Loading/Reading a Data Set from a File
- Displaying Data
- Getting Information About the Size of the Data
- Sampling in Data
- Data Types in the Data
- Obtaining Basic Statistical Information
Data Preprocessing and Cleaning
- Getting to Know the Data
- Viewing and Selecting Attributes
- Sorting and Grouping
- Operations on Attributes
- Operations on Observations
- Data Filtering
- Missing Data
- Duplicate Data
- Data Transformation Operations
- Detecting Outliers/Extreme Values
Exploratory Data Analysis
- Overview of the Data
- Data Selection
- Data Preprocessing
- Data Cleaning
- Using the re (regular expression) Module in Data Analysis
- Statistical Operations on Numerical Data
Data Visualization
- Drawing charts (line, bar, pie, heatmap, etc.)
- Working with charts
Prerequisites
There are no prerequisites for this course.
Related Courses and Quote
For broader machine learning and big data coverage, see Data Science and Big Data Analytics Training; for a focus on model development, see Machine Learning and Applications with Python Training.
To get a training plan and price quote for your organization, fill out the contact form on this page. For other ways to reach us, use the BlueMark Academy contact page.
Frequently Asked Questions
How Long Is the Data Literacy Training?
The training lasts 4 days.
Is the Training Online?
The training is delivered live online or in person.
Are There Prerequisites for Attending?
The current program information states that there are no prerequisites.
Does the Training Include Hands-On Python Topics?
Yes. Loading data from files, displaying data, sampling, data types and basic statistics are covered as part of the Python-based data literacy exercises.
Which Data Analysis Tools Are Covered?
Pandas, NumPy, Matplotlib and Seaborn are part of the curriculum. Data preprocessing, exploratory analysis and visualization are also covered in the program.
How Can We Get a Quote for Our Team?
Send us your team’s training needs through the contact form on this page to request a training plan and price quote.