Geared for scientists and engineers with limited practical programming background or experience, Applied Python for Data Science & Engineering is a hands-on introductory-level course that provides a ramp-up to using Python for scientific and mathematical computing. Students will explore basic Python scripting skills and concepts, and then explore the most important Python modules for working with data, from arrays, to statistics, to plotting results. Prior scripting experience is helpful but not required.
This course is approximately 50% hands-on, combining expert lecture, real-world demonstrations and group discussions with machine-based practical labs and exercises. Our engaging instructors and mentors are highly experienced practitioners who bring years of current "on-the-job" experience into every classroom. Working in a hands-on learning environment, guided by our expert team, attendees will learn how to:
- Learn essentials Python scripting methods to create and run basic programs
- Design and code modules and classes
- Implement and run unit tests
- Use benchmarks and profiling to speed up programs
- Process XML, JSON, and CSV
- Manipulate arrays with NumPy
- Get a grasp of the diversity of subpackages that make up SciPy
- Use Series and Dataframes with Pandas
- Use Jupyter notebooks for ad hoc calculations, plots, and what-if?
Need different skills or topics? If your team requires different topics or tools, additional skills or custom approach, this course may be further adjusted to accommodate. We offer additional python, data science, AI, machine learning , web development, data science, machine learning and other related topics that may be blended with this course for a track that best suits your needs. Our team will collaborate with you to understand your needs and will target the course to focus on your specific learning objectives and goals.
This course is geared for data analysts, developers, engineers or anyone tasked with utilizing Python for data analytics tasks. While there are no specific programming prerequisites, students should be comfortable working with files and folders and the command line. Prior scripting experience is helpful but not required.
Our core Python and data science training courses provide students with a solid foundation for continued learning based on role, goals, or their areas of specialty. Our learning paths offer a wide variety of related follow-on courses. Please see the Related Courses tab for specific Pre-Requisite courses, Related Courses that offer similar skills or topics, and next-step Learning Path recommendations.
Student Materials: Each participant will receive a Student Guide with course notes, code samples, software tutorials, step-by-step written lab instructions, diagrams and related reference materials and resource links. Students will also receive the project files (or code, if applicable) and solutions required for the hands-on work. Any courseware of lab materials provided in a cloud (if applicable) will also be made available to you separately.
Hands-On Setup Made Simple! Our dedicated tech team will work with you to ensure our ‘easy-access’ cloud-based course environment, or local installation, is accessible, fully-tested and verified as ready to go well in advance of the course start date, ensuring a smooth start to class and effective learning experience for all participants. We can also help you install this course locally if preferred. Please inquire for details and options.
Every-Course Extras = High-Value & Long-Term Learning Support! All Public Schedule courses include our unique EveryCourse Extras package (Post-Course Resource Site access with Review Labs & Live Instructor Follow-on Support, access to QuickSkills recorded High-Value lessons, Free *Live* Course Refresh Re-Takes, early access to Special Offers, Free Courses & more). Please inquire for details.