Ementorhub

What you'll learn

Demonstrate proficiency in data science and machine learning techniques using a real-world data set and prepare a report for stakeholders

Apply your skills to perform data collection, data wrangling, exploratory data analysis, data visualization model development, and model evaluation

Write Python code to create machine learning models including support vector machines, decision tree classifiers, and k-nearest neighbors

Evaluate the results of machine learning models for predictive analysis, compare their strengths and weaknesses and identify the optimal model

Skills you'll gain

Data Science

Web Scraping

Data Wrangling

Plotly

Data-Driven Decision-Making

Data Presentation

Pandas (Python Package)

Statistical Modeling

Data Analysis

Exploratory Data Analysis

Data Collection

Machine Learning Methods

Predictive Modeling

There are 5 modules in this course

In this course you will assume the role of a Data Scientist working for a startup intending to compete with SpaceX, and in the process follow the Data Science methodology involving data collection, data wrangling, exploratory data analysis, data visualization, model development, model evaluation, and reporting your results to stakeholders. You will be tasked with predicting if the first stage of the SpaceX Falcon 9 rocket will land successfully. With the help of your Data Science findings and models, the competing startup you have been hired by can make more informed bids against SpaceX for a rocket launch. In this course, there will not be much new learning, instead you’ll focus on hands-on work to demonstrate and apply what you have learnt in previous courses. By successfully completing this Capstone you will have added a project to your data science and machine learning portfolio to showcase to employers.

Exploratory Data Analysis (EDA)

Interactive Visual Analytics and Dashboard

Predictive Analysis (Classification)

Present Your Data-Driven Insights