Course

Applied Data Science Capstone

IBM

This Applied Data Science Capstone is the final project in the IBM Data Science Professional Certificate. Through real-life scenarios, you'll apply data science methodology, including data collection, wrangling, visualization, and model development, to predict the success of SpaceX Falcon 9 rocket landings.

What You'll Learn:

  • Demonstrate proficiency in data science and machine learning techniques using real-world data
  • Apply skills in data collection, wrangling, exploratory data analysis, visualization, and model development
  • Write Python code to create machine learning models (e.g., support vector machines, decision tree classifiers, k-nearest neighbors)
  • Evaluate and compare the results of machine learning models for predictive analysis

Certificate Available ✔

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Applied Data Science Capstone
Course Modules

This course is divided into five modules: Introduction, Exploratory Data Analysis (EDA), Interactive Visual Analytics and Dashboard, Predictive Analysis (Classification), and Present Your Data-Driven Insights. Each module focuses on specific aspects of the data science methodology, including hands-on labs and quizzes.

Introduction

This module introduces the project scenario and overview, data collection, and data wrangling. It also includes hands-on labs and quizzes to apply the learned concepts.

Exploratory Data Analysis (EDA)

This module focuses on exploratory data analysis using SQL and data visualization. It includes hands-on labs and checkpoints to reinforce the concepts.

Interactive Visual Analytics and Dashboard

This module covers interactive visual analytics and dashboards. It includes a graded quiz and hands-on labs for practical application of the concepts.

Predictive Analysis (Classification)

This module delves into predictive analysis, including a graded quiz and hands-on lab for machine learning prediction.

Present Your Data-Driven Insights

This module provides guidance on presenting data-driven insights, including best practices for reporting findings and preparing presentations.

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