Introduction to Data Science in Python
Learn Python basics and explore data manipulation using Pandas to clean, analyze, and visualize tabular data.
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Showing 26–50 of 60 items
Learn Python basics and explore data manipulation using Pandas to clean, analyze, and visualize tabular data.
Master text cleaning, classification, and topic modeling using Python and NLP to extract meaning from large text datasets.
Learn to fit statistical models using Python and apply regression, Bayesian, and mixed-effects methods to real data.
Learn Python and Rhino scripting to create computational design workflows and generate geometric forms through coding and procedural design.
Learn how to integrate Meta’s Llama 2 into Python workflows using prompting, quantization, and open-source LLMs for generative AI.
Retrieve and process complex web data using Python APIs, list comprehensions, and build a real-world tag recommendation system.
Este curso presentará las estructuras de datos centrales del lenguaje de programación Python. Pasaremos por los conceptos básicos de la programación de procedimientos y exploraremos cómo podemos usar
Apply Python and scientific libraries like NumPy and SciPy to solve statistical problems and explore probability, distributions, and relationships in data.
Build foundational Python skills for data analysis, web applications, and practical computing tasks.
Develop data science skills in Python, including data wrangling, visualization, machine learning, and applied analytics.
Learn Python 3 programming fundamentals for problem-solving, software development, and automation.
Use Python to perform statistical analysis, test hypotheses, and interpret real-world data effectively.
Use Python for creative coding projects that blend programming, visual art, interactivity, and computational thinking.
This Specialization builds on the success of the Python for Everybody course and will introduce fundamental programming concepts including data structures, networked application program interfaces, an
This Specialization builds on the success of the Python for Everybody course and will introduce fundamental programming concepts including data structures, networked application program interfaces, an
Strengthen Python programming with data structures, problem-solving strategies, and effective debugging techniques.
Advance Python data science skills with deeper machine learning, text mining, and applied analytics techniques.
Learn to write and understand object-oriented programs in Python using real-world modeling and creative coding projects.
Learn web application fundamentals using Django, covering HTTP, HTML, MVC, and live deployment techniques.
Explore database modeling, SQL, and Django’s ORM to build scalable, interactive web applications using Python.
Learn to use Python in Rhino 3D to create complex geometric forms through procedural logic and design computation.
Apply machine learning techniques to real sports data to analyze, predict outcomes, and enhance performance analytics.
Use logistic regression and Python to model and predict sports outcomes while examining analytics in gambling and society.
Learn NumPy and pandas to manipulate arrays and write efficient Python code for numerical computing and data analysis.
Learn to use AI tools like ChatGPT to analyze, visualize, and interpret data for real-world applications and projects.