End-to-End Machine Learning
Dive into the world of machine learning and discover how to design, train, and deploy end-to-end models.
Follow short videos led by expert instructors and then practice what you’ve learned with interactive exercises in your browser.
Dive into the world of machine learning and discover how to design, train, and deploy end-to-end models.
Learn to connect Tableau to different data sources and prepare the data for a smooth analysis.
Learn to acquire data from common file formats and systems such as CSV files, spreadsheets, JSON, SQL databases, and APIs.
In this course, you will use T-SQL, the flavor of SQL used in Microsofts SQL Server for data analysis.
Learn to clean data as quickly and accurately as possible to help your business move from raw data to awesome insights.
Find tables, store and manage new tables and views, and write maintainable SQL code to answer business questions.
Data visualization is one of the most desired skills for data analysts. This course allows you to present your findings better using Tableau.
Start your reinforcement learning journey! Learn how agents can learn to solve environments through interactions.
Create new features to improve the performance of your Machine Learning models.
Unlock more advanced AI applications, like semantic search and recommendation engines, using OpenAIs embedding model!
Learn the fundamentals of AI security to protect systems from threats, align security with business goals, and mitigate key risks.
Learn to create your own Python packages to make your code easier to use and share with others.
Learn the key components of building a strong data culture within an organization.
Building on your foundational Power Query in Excel knowledge, this intermediate course takes you to the next level of data transformation mastery
In this four-hour course, you’ll learn the basics of analyzing time series data in Python.
Unlock BigQuerys power: grasp its fundamentals, execute queries, and optimize workflows for efficient data analysis.
This course focuses on feature engineering and machine learning for time series data.
Gain an introduction to data governance, exploring its meaning, purpose, and how to implement a data governance framework.
In this course, you will be introduced to unsupervised learning through techniques such as hierarchical and k-means clustering using the SciPy library.
Apply PyTorch to images and use deep learning models for object detection with bounding boxes and image segmentation generation.
In this course you will learn the basics of machine learning for classification.
Discover how to make better business decisions by applying practical data frameworks—no coding required.
Learn the fundamentals of neural networks and how to build deep learning models using TensorFlow.
Learn how to blend business, data, and AI, and set goals to drive success with an effectively scalable AI Strategy.
Learn about string manipulation and become a master at using regular expressions.
Learn essential data structures such as lists and data frames and apply that knowledge directly to financial examples.
Learn how to use MLflow to simplify the complexities of building machine learning applications. Explore MLflow tracking, projects, models, and model registry.
In this course you will learn the details of linear classifiers like logistic regression and SVM.
Build on top of your Python skills for Finance, by learning how to use datetime, if-statements, DataFrames, and more.
Master the key concepts of data management, from life cycle stages to security and governance.