Our Introduction to Python course is designed to take complete beginners or experienced developers up to speed on Python’s capabilities, setting up students for success in using Python for their specific field of expertise.

Whether you have never programmed before, already know basic syntax, or want to learn about the advanced features of Python, this course is for you! In this course we will teach you Python 3. Learn how to use Python for real-world tasks, such as working with PDF Files, sending emails, reading Excel files, scraping websites for information, working with image files, and much more! This course will teach you Python in a practical manner and provides a full coding screencast and a corresponding code notebook to review the concepts and exercises conducted in class.

Please note, this course is able to be offered in either 3 full day sessions or 5 partial day sessions. See the schedule below.

This course includes 6-months access to the full course content in on-demand format to support post-class reference and review.

This course will teach you to use Microsoft Power Platform solutions to simplify, automate, and empower business processes for organizations in the role of a Functional Consultant. A Microsoft Power Platform Functional Consultant is responsible for creating and configuring apps, automations, and solutions. They act as the liaison between users and the implementation team. The functional consultant promotes utilization of solutions within an organization. The functional consultant may perform discovery, engage subject matter experts and stakeholders, capture requirements, and map requirements to features. They implement components of a solution including application enhancements, custom user experiences, system integrations, data conversions, custom process automation, and simple visualizations. This course may contain a 1-day Applied Workshop. This workshop will allow you to practice your Functional Consultant skills by creating an end-to-end solution to solve a problem for a fictitious company. The solution will include a Microsoft Dataverse database, Power Apps canvas app, and Power Automate flows.

Data Science is the critical skill of the modern workforce. Data science skills allow for the extraction of key insights and relevant knowledge from large datasets. This data science training course is for Python developers who want to learn how to use the key libraries in the Python Data Science ecosystem. This course covers NumPy for numerical data processing, Pandas for data analysis, and Matplotlib and Seaborn for quick visualizations and statistical reporting. The training is all conducted in a modern Jupyter Notebook format, allowing students to read and write code directly within our training notebooks.

You’ll learn everything you need to know for the full data science tech stack required to work at the world’s top companies. This Python for Data Science course takes a structured approach that will guide you through understanding not just how to use data science, but why we use them by providing a balance between practical real world case studies and mathematical theory behind the data science algorithms.

Please note, this course is able to be offered in either 3 full day sessions or 5 evening sessions. See the schedule below.

This course includes 6-months access to the full course content in on-demand format to support post-class reference and review.

Master the skills to use machine learning in your day-to-day work with this Python course. Create algorithms to predict classes, continuous values, and more.

This course is designed for the student who already knows some Python and is ready to dive deeper into using those Python skills for Machine Learning. With a focus on SciKit Learn, you’ll learn all aspects of Machine Learning ranging from a variety of regression types (Linear / Lasso /Ridge), Elastic Net, K Nearest Neighbors and Means Clustering, Hierarchal Clustering, DBSCAN, PCA, and Model Deployment.

This course includes 6-months access to the full course content in on-demand format to support post-class reference and review.