Build a TikTok Data Science App with Streamlit and Python - Data Science Project

Overview

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Embark on a comprehensive tutorial to create a sophisticated TikTok data science application using Streamlit and Python. Learn to build a real-time feed from TikTok, preprocess data through an ETL pipeline, and visualize insights with a Streamlit dashboard. Follow step-by-step instructions to set up a virtual environment, install necessary APIs, and utilize VS Code for development. Explore data extraction from TikTok, JSON exporting, and Jupyter notebook prototyping. Master pandas for data manipulation, construct an ETL pipeline, and convert it into a reusable module. Dive into Streamlit app development, incorporating TikTok hashtag search functionality and creating interactive Plotly charts. Gain practical experience in data science project implementation while addressing client needs through simulated conversations. Access provided GitHub repository for code references and connect with the instructor through various social media platforms for further support and discussions.

Syllabus

- Start
- Introduction
- Gameplan
- Client Conversation 1
- Tutorial Start
- Creating a Virtual Environment
- Installing the TikTok API
- Setup VS Code
- Getting Data from TikTok
- Exporting Data to JSON
- Client Conversation 2
- Setting Up Jupyter for Prototyping
- Loading TikTok Data into Pandas
- Building an ETL Pipeline
- Viewing Transformed Data in Pandas
- Converting ETL code into a Module
- Exporting Transformed TikTok Data to CSV
- Client Conversation 3
- Setting up Streamlit
- Building Your First Streamlit App
- Adding TikTok Hashtag Search
- Creating Plotly Charts
- Setting app to wide and Creating a sidebar
- Client Conversation 4
- Wrap up