Data science courses

Visualize seasonality, trends and other patterns in your time series data.

In this course youll learn to use and present logistic regression models for making predictions.

Learn how to approach and win competitions on Kaggle.

Explore ways to work with date and time data in SQL Server for time series analysis

Learn key object-oriented programming concepts, from basic classes and objects to advanced topics like inheritance and polymorphism.

Detect anomalies in your data analysis and expand your Python statistical toolkit in this four-hour course.

Julia is a new programming language designed to be the ideal language for scientific computing, machine learning, and data mining.

Learn how to use spaCy to build advanced natural language understanding systems, using both rule-based and machine learning approaches.

Orchestrate data using unions, joins, parsing, and performance optimization in Alteryx.

Learn to build recommendation engines in Python using machine learning techniques.

Learn to use essential Bioconductor packages for bioinformatics using datasets from viruses, fungi, humans, and plants!

Learn to design and run your own Monte Carlo simulations using Python!

Learn the gritty details that data scientists are spending 70-80% of their time on; data wrangling and feature engineering.

Explore the concepts and applications of linear models with python and build models to describe, predict, and extract insight from data patterns.

Get to know the Google Cloud Platform (GCP) with this course on storage, data handling, and business modernization using GCP.

In this course, youll learn the basics of relational databases and how to interact with them.

In this course youll learn about basic experimental design, a crucial part of any data analysis.

Understand the role and real-world realities of Explainable Artificial Intelligence (XAI) with this beginner friendly course.

Begin your journey with Scala, a popular language for scalable applications and data engineering infrastructure.

Learn fundamental probability concepts like random variables, mean and variance, probability distributions, and conditional probabilities.

Learn about MLOps architecture, CI/CD/CM/CT techniques, and automation patterns to deploy ML systems that can deliver value over time.

In this case study, you’ll use visualization techniques to find out what skills are most in-demand for data scientists, data analysts, and data engineers.

Learn and use powerful Deep Reinforcement Learning algorithms, including refinement and optimization techniques.

Learn about the challenges of monitoring machine learning models in production, including data and concept drift, and methods to address model degradation.

Learn how to make predictions about the future using time series forecasting in R including ARIMA models and exponential smoothing methods.

Learn how to use Python scripts in Power BI for data prep, visualizations, and calculating correlation coefficients.

Master SQL Server programming by learning to create, update, and execute functions and stored procedures.

Learn to analyze data over time with this practical course on Time Series Analysis in Power BI. Work with real datasets & practice common techniques.

Learn to solve real-world optimization problems using Pythons SciPy and PuLP, covering everything from basic to constrained and complex optimization.

Gain a clear understanding of GDPR principles and how to set up GDPR-compliant processes in this comprehensive course.