This professional certificate course is an 11-month online course and consists of 9 online courses and 1 capstone project.

In this Professional Certificate, I developed and honed hands-on skills in Data Science and Machine Learning. I first learnt about the orientation and methodology of data science, became familiar and used a variety of data science tools, learned Python and SQL, performed EDA, Data Visualization, Analysis, Dashboarding, and created and evaluated various Machine Learning models like linear regression, polynomial regression, KNN, decision trees, logistic regression, SVM, recommendation systems and clustering.

I worked with online tools like JupyterLab, GitHub, R Studio, Watson Studio. Throughout the course, I gained experiences with many python libraries: the scientific and computing libraries Pandas and NumPy; Matplotlib, Seaborn, Folium for data visualization, machine learning libraries like Scikit-learn, SciPy, and many more.

Following are some of the projects that I completed as part of the course:

• Extract and graph financial data with the Pandas Python library - Project Presentation
• Querying census, crime, and school demographic data sets using SQL - Source Code
• Wrangle data, graph plots, and create regression models to predict housing prices with data science Python libraries - House Sales in King County USA
• Create a dynamic Python dashboard to monitor, report, and improve US domestic flight reliability - US Domestic Airline Flight Performance Interactive Dashboard
• Apply and compare machine learning classification algorithms to predict whether a loan case will be paid off or not - Source Code
• Train and compare machine learning models to predict if a space launch can reuse the first stage of a rocket
  • Project Presentation
  • SpaceX Launch Records Interactive Dashboard

Certificate:

• IBM Data Science Professional Certificate
• 10 Course Certificates