Complete Guide to Data Science Applications with Streamlit
What you'll learn
- Building Data Applications with Streamlit
- Integrating Matptlotlib & Seaborn in Streamlit
- Plotly Visualizations in Streamlit
- Authenticating Streamlit Applications
- Deploying Streamlit Applications
- Using Streamlit Components
- Altair Visualizations in Streamlit
- Basic Python Programming, however a Python crash course is included
Analyzing data and building machine learning models is one thing. Packaging these analyses and models such that they are sharable is a different ball game altogether.
This course aims at teaching you the fastest and easiest way to build and share data applications using Streamlit. You don't need any experience in building front-end applications for this. Here are some of the things you can expect to cover in this course:
Python Crash Course
NumPy Crash Course
Introduction to Streamlit
Integrating Matplotlit and Seaborn in Streamlit
Using Altair and Vega-Lite in Streamlit
Understand all Streamlit Widgets
Upload and Process Files
Build an Image Processing Application
Develop a Natural Language Processing Application
Integrate Maps with Streamlit
Implement Plotly Graphs
Authenticate Your Applications
Laying Out your Application in Streamlit
Developing with Streamlit Components
Deploying Data Applications
At the end of the course, you will have built several applications that you can include in your data science portfolio. You will also have a new skill to add to your resume.
The course also comes with a 30-day money-back guarantee. Enroll now and if you don't like it you will get your money back no questions asked.
Who this course is for:
- Individuals interested in building data science and machine learning applications in Python
Derrick Mwiti is a data scientist who has a great passion for sharing knowledge. He is an avid contributor to the data science community via blogs such as Heartbeat, Towards Data Science, Datacamp, Neptune AI, KDNuggets just to mention a few. Derrick is also an author and online instructor. He also trains and works with various institutions to implement data science solutions as well as to upskill their staff.
Derrick’s studied Mathematics and Computer Science from the Multimedia University, he also is an alumnus of the Meltwater Entrepreneurial School of Technology.
When Derrick is not staring at his computer, he enjoys reading and traveling
Namespace Labs is committed to advancing the data science field by sharing the latest tools and technologies. Our bid is to create content that help new people entering the field as well as advance the skills of those in the field. We also aim at building data science solutions that eliminate redundancies, offer useful business insights, and help businesses achieve customer satisfaction through speedy, quality service delivery.