Data Wrangling Academy – Spring 2024

Join the Data Wrangling Professional program and take your data analysis skills to the next level!

Course Overview

The Data Wrangling Professional program is designed to equip participants with the skills and knowledge necessary to effectively collect, clean, and transform data for analysis. This course covers essential techniques and tools used in the data wrangling process, enabling professionals to handle real-world data challenges and prepare data for advanced analytics and decision-making.

Program Objectives

By the end of this program, participants will be able to:

1. Understand the importance of data wrangling in the data analysis process.
2. Collect data from various sources, including databases, APIs, and web scraping.
3. Clean and preprocess data to ensure quality and consistency.
4. Transform data for analysis using advanced techniques and tools.
5. Utilize popular data wrangling libraries and frameworks.
6. Handle missing data, outliers, and data inconsistencies.
7. Prepare data for visualization and machine learning applications.

Target Audience

This program is ideal for:

• Data analysts and scientists who need to preprocess data for analysis.
• Business analysts looking to improve their data handling skills.
• IT professionals and software developers involved in data management.
• Students and recent graduates aiming to enter the field of data analytics.

Course Profile: Data Wrangling Professional Program

Prerequisites

Participants should have:

• Basic knowledge of Python programming .
• Familiarity with spreadsheet software (e.g., Microsoft Excel).
• Not Required: Understanding of basic statistics and data analysis concepts.

Course Modules

Module 1: Introduction to Data Wrangling

• Overview of data wrangling and its significance
• The data wrangling pipeline
• Case studies of data wrangling in various industries

Module 2: Data Collection

• Accessing data from databases (SQL)
• Web scraping techniques and tools
• Extracting data from APIs

Module 3: Data Cleaning

• Data Preprocessing
• Identifying and handling missing data
• Dealing with duplicates and inconsistencies
• Data type conversions and parsing dates
• Dealing With outliers
• Visual Inspection and Dealing with Wrong Entries
• Dealing With Categorical Variables
• Special Topics For Data Processing (SQL, Stats,and More)

Module 4: Data Transformation & Feature Selection

• Reshaping data: pivoting and unpivoting
• Merging and joining datasets
• Data aggregation and summarization
• Data Transformation using SciKit Learn Library for;

• • Rescaling
  • Standardization
  • Normalization
• Feature Selection & Engineering

Module 5: Advanced Data Wrangling Techniques

• Handling large datasets with efficient techniques
• Data wrangling with Python libraries: Pandas, NumPy
• Using advanced libraries for data processing and cleaning

Module 6: Practical Applications and Projects

• Real-world data wrangling case studies
• Hands-on projects and assignments
• Preparing data for visualization and machine learning

Tools and Technologies

• Python: Pandas, NumPy, BeautifulSoup, Requests and more
• JupyterLab
• SQL: Basic to advanced SQL queries
• Excel: Advanced functions and data manipulation techniques

Evaluation and Certification

Participants will be assessed through:

• Quizzes and assignments for each module
• A capstone project demonstrating data wrangling skills
• Final exam

Upon successful completion, participants will receive a "Data Wrangling Professional" certificate, recognizing their proficiency in data wrangling techniques and tools.

Course Duration

The program is designed to be completed over 10 weeks, with a combination of online lectures, hands-on exercises, and project work.

Enrollment

If the 'Apply for Course' button is active you may enroll apply for enrollment to this course now. For enrollment details and course schedules, please visit our website or contact our admissions office.

Contact Information

• Email: admissions@onecampusacademy.com
• Phone: +1 (475) 209-1037
• Website: learn.onecampusacademy.com