About Specialization Applied Data Science course
This action-packed specialization is designed for data science enthusiasts who want to gain hands-on skills to solve real-world data problems. If you are interested in a career in data science and already have basic skills or have completed
specialization "Introduction to Data Science", this program is for you!
This 4-course specialization will give you the tools you need to analyze data and make data-driven business decisions using computer science and statistical analysis. You'll learn Python—no prior programming knowledge is required—and become familiar with data analysis and visualization techniques. You'll use tools used by real data scientists like Numpy and Pandas, practice predictive modeling and model selection, and learn how to tell a compelling story using data to make decisions.
Through lectures, labs, and projects on the IBM Cloud, you'll gain hands-on experience solving interesting data problems from start to finish. Take this specialization to strengthen your Python and data science skills before diving into big data, artificial intelligence, and deep learning.
In addition to a certificate of completion from Coursera, you will also receive a digital badge from IBM . This Specialization can also be used to obtain
IBM Data Science Professional certificate.
This program is ACE® recommended and can earn up to 12 college credits upon completion.
Applied Learning Project
Build your data science portfolio as you gain hands-on experience creating artifacts in interactive labs and projects throughout the program. These courses include real-world projects using basic data science tools to apply your acquired skills. Projects:
Extract and plot financial data using the Pandas Python library.
Extract data, graph, and build regression models to predict home prices using Python libraries including NumPy and Sklearn.
Create visualizations and dynamic dashboards in Python with tree and line graphs using libraries such as Matplotlib, Seaborn, and Plotly Dash to monitor, report, and improve reliability of US domestic flights.
In your final Capstone course, apply everything you've learned in previous courses into one comprehensive project. You will train and compare machine learning models, including support vector machines, classification trees, and logistic regression, to predict whether SpaceX will be able to reuse the first stage of a rocket at launch.
