In this final capstone course, you will transition from learning to applying data science and machine learning techniques to real-world scenarios. You will assume the role of a Data Scientist tasked with solving a business problem, such as predicting the success of a SpadeX Falcon 9 rocket landing. Through hands-on work, you will demonstrate proficiency in data collection, wrangling, explanatory analysis, visualization, model development, and evaluation.

The course offers an opportunity to work with real datasets, like New York City’s 311 complaints, and tackle questions that can help improve the Department of Housing Preservation and Development operations. You will use Python and machine learning models like support vector machines and decision trees, evaluate model performance, and refine your approach.

By the end of the course, you will have created a showcase project that not only demonstrates your data science skills but also positions you as a competitive candidate in the job market. Upon successful completion, you will earn a skill badge to highlight your expertise to potential employers.

You will learn about:

Applying data science methodologies to solve real-world problems.

Building and evaluating machine learning models, including support vector machines and decision trees.

Using Python and Jupyter Notebooks for hands-on data analysis.

Presenting your findings and making data-driven decisions based on your analysis.

Enroll today and kickstart your data analytics career... You have a lot to look forward to!

PREREQUISITES: This is a beginner-friendly introduction to data analysis; therefore, no prior experience is necessary. However, basic knowledge of using a computer, navigating files and folders, and using basic software applications is recommended.

IBM Data Analyst Professional Certificate

This course is part of the IBM Data Analyst Professional Certificate. If you’re keen to kickstart a career in data analytics, we recommend you enroll for the full Professional Certificate program and work through the courses in order. Within just a few months, you’ll have job-ready skills and practical experience on your resume that will catch the eye of an employer!

Course Syllabus

Module 1: Introduction

Project Scenario and Overview
Data Collection Overview
Data Wrangling Overview

Module 2: Explanatory Data Analysis (EDA)

Explanatory Data Analysis Overview

Module 3: Interactive Visual Analytics and Dashboard

Interactive Visual Analytics and Dashboard

Module 4: Predictive Analysis (Classification)

Predictive Analysis Overview

Module 5: Present Your Data-Driven Insights

Elements of a Successful Data Finding Report
Best Practices for Presenting Your Findings

What You'll Learn

Apply the knowledge of data science and machine learning to solve real-world scenarios.
Perform data collection, wrangling, and explanatory data analysis using Python.
Develop and validate predictive machine learning models, such as support vector machines and decision tree classifiers, using Python.
Analyze and visualize data, leveraging Python to generate actionable insights.
Evaluate machine learning models, comparing their performance to identify the optimal model for predictive analysis.

Recommended Skills Before Taking this Course

To get the most out of this course, you should have completed the following courses or have proficiency in these topics: Python Basics for Data Science, Analyzing Data with Python, Visualizing Data with Python, and Machine Learning with Python.

Data Science Capstone Project

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