Course Overview
Want to master the full data science lifecycle and land real-world data projects?
This hands-on course is designed to take you from data wrangler to insight generator, walking you through every essential phase of the data science workflow.
By the end of this course, you'll know how to manage real data projects from start to finish—no guesswork, no gaps.
Throughout the course, we’ll cover key stages and tools, including:
Problem Formulation (Understanding the business need)
Data Collection & Cleaning (Using Python, Pandas, and APIs)
Exploratory Data Analysis (Uncovering trends and patterns with visualization)
Feature Engineering (Transforming raw data into model-ready formats)
Model Building (Using Scikit-learn, XGBoost, and more)
Model Evaluation & Tuning (Improving model performance)
Deployment (Putting your models into production using Flask or Streamlit)
Monitoring & Maintenance (Tracking performance over time)
What you will learn
Data collection using web scraping and APIs.
Data preprocessing and cleaning with Python.
Data visualization using libraries like Matplotlib and Seaborn.
Storing and managing data with SQL databases.
Model development, evaluation, and deployment using machine learning tools.
FINAL PROJECT: Build and deploy a complete data science solution from raw data to actionable insights.
Course Curriculum
26
Lessons
(
6 hours
)
Course Review
Gonzalo
The 'End-to-End Data Science Workflow' course provided a comprehensive guide to handling real-world data science projects. From data collection to model deployment, every step was explained in clear detail. I appreciated the hands-on approach, especially the use of Python and its libraries. This course is a great starting point for anyone looking to build a solid foundation in data science.
Casilo
I found the 'End-to-End Data Science Workflow' course incredibly insightful. The practical applications were well balanced with theoretical knowledge, giving me the skills to tackle real-world data science problems. The module on model deployment was particularly helpful. I'd highly recommend this course to anyone serious about mastering the full data science process.
