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By continuing, you accept our Terms of Use, our Privacy Policy and that your data is stored in the USA.Learn to solve real-world optimization problems using Pythons SciPy and PuLP, covering everything from basic to constrained and complex optimization.
Extend your regression toolbox with the logistic and Poisson models and learn to train, understand, and validate them, as well as to make predictions.
Leverage the power of Python and PuLP to optimize supply chains.
Learn to conduct image analysis using Keras with Python by constructing, training, and evaluating convolutional neural networks.
Build AI teams that work together, automate workflows, and generate content with CrewAI.
Learn to build recommendation engines in Python using machine learning techniques.
Learn the fundamentals of exploring, manipulating, and measuring biomedical image data.
Learn to build pipelines that stand the test of time.
Discover how to talk to your data using text-to-query AI agents with MongoDB and LangGraph.
Explore the concepts and applications of linear models with python and build models to describe, predict, and extract insight from data patterns.
This course covers everything you need to know to build a basic machine learning monitoring system in Python
Build AI agentic workflows that can plan, search, remember, and collaborate, using LlamaIndex.
Explore association rules in market basket analysis with Python by bookstore data and creating movie recommendations.
Learn how to develop deep learning models with Keras.
Build real-world applications with Python—practice using OOP and software engineering principles to write clean and maintainable code.
Learn how to load, transform, and transcribe speech from raw audio files in Python.
Learn how to use Python to analyze customer churn and build a model to predict it.
Learn how to segment customers in Python.
Learn how to use Python to create, run, and analyze A/B tests to make proactive business decisions.
Master RAG with Weaviate! Embed text and images for retrieval, and experiment with vector, BM25, and hybrid search.
Sharpen your knowledge and prepare for your next interview by practicing Python machine learning interview questions.
Create a healthcare AI agent using Haystack, an open-source framework for orchestrating LLMs and external components.
Learn efficient techniques in pandas to optimize your Python code.
Learn to analyze financial statements using Python. Compute ratios, assess financial health, handle missing values, and present your analysis.
Learn to solve increasingly complex problems using simulations to generate and analyze data.
Explore the Stanford Open Policing Project dataset and analyze the impact of gender on police behavior using pandas.
Get hands-on experience making sound conclusions based on data in this four-hour course on statistical inference in Python.
Learn about GARCH Models, how to implement them and calibrate them on financial data from stocks to foreign exchange.
Learn how to use RNNs to classify text sentiment, generate sentences, and translate text between languages.
Learn how bonds work and how to price them and assess some of their risks using the numpy and numpy-financial packages.