
Learn to import lab data into Jupyter notebooks using pandas, access and manipulate the data, and create plots with customized labels for effective data analysis and visualization.

Learn to fine-tune pre-trained transformer models for question-answering using HuggingFace and PyTorch. Gain practical skills in NLP and unlock the power of transformers for custom Q&A applications.

Explore efficient similarity search using Locality Sensitive Hashing (LSH) and Random Projection. Learn how to handle large-scale data and implement approximate search techniques in Python.

Discover how Teradata VantageCloud and Azure ML integration accelerates AI and ML insights at scale, overcoming deployment challenges and unlocking data-driven value for organizations.

Learn to build a real-time TikTok data analytics dashboard using Python, Streamlit, and Plotly. Covers data extraction, ETL pipeline creation, and interactive visualization techniques.

Comprehensive Python tutorial covering fundamentals, data structures, control flow, functions, OOP, modules, file handling, and math operations, with practical data science applications and projects.

Learn Python conditions and loops for data science, covering if-else statements, logical operators, loop types, and iterating through lists and dictionaries with practical applications.

Learn essential Python concepts for data science: variables, data types, lists, and dictionaries. Gain practical skills through hands-on examples and clear explanations.

Learn Python for data science: set up Jupyter Notebooks, understand its basics, write your first code, and explore Python in various environments. Perfect for beginners starting their data science journey.

Learn to build multi-page Python web apps with Streamlit's new native support. Covers setup, demo, project structure, code walkthrough, page reordering, and live app creation.

Learn to build a GitHub Stars History Tracker using Python and Streamlit. Create an end-to-end web app that visualizes repository star data, from design to deployment on Streamlit Cloud.

Learn to deploy LayoutLMv3 for document classification using Streamlit and HuggingFace Spaces. Covers model loading, input preparation, and classification process, resulting in a functional demo app.

Learn to manipulate geotiff files using rasterio in Python, including reading, plotting, and performing NDVI calculations. Gain practical skills for working with satellite imagery and geospatial data analysis.

Explore implementing filters in Haystack's new document store, covering filter utilities, writing and testing filters, and integrating them into the pipeline.

Explore Haystack's new document store with hands-on demos covering initialization, document management, QA pipeline, and metadata filtering for efficient information retrieval.

Explore Faiss indexes for efficient similarity search, comparing Flat, LSH, HNSW, and IVF to optimize performance in large-scale datasets. Learn to choose and implement the best index for your needs.

Learn web scraping with Python to create a Disney movie dataset, covering BeautifulSoup, data cleaning, APIs, and various Python libraries for real-world data science tasks.

Learn to generate realistic mock sales data using Python libraries like NumPy, Pandas, and Datetime. Create datasets with varied product purchases, timestamps, and addresses for data science practice.

Learn to create and customize line graphs and bar charts using Matplotlib in Python, covering essential visualization techniques like styling, scaling, and annotating plots.

Learn advanced Streamlit techniques for building Python web apps. Covers tips, tricks, components, and automation with Google Sheets and Firebase to enhance app functionality and user experience.

Learn to build a Speech-to-Text Transcription App using AssemblyAI API and Streamlit. Create a command-line tool and web app to transcribe YouTube videos with Python.