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Applied Python for Data Science & Engineering
Description
Applied Python for Data Science & Engineering Introduction
Welcome to our course, “Applied Python for Data Science & Engineering,” a dynamic program crafted to empower professionals from various backgrounds, including scientists, engineers, data analysts, developers, and coding novices, with essential Python programming skills tailored for success in the realms of data science and engineering.
Throughout this course, our primary objective is to furnish you with the indispensable Python expertise crucial for thriving in your respective fields. We understand that Python serves as the cornerstone for numerous data-driven endeavors, and thus, our curriculum is meticulously designed to bridge the gap between theory and application.
Our course structure revolves around an immersive, hands-on learning experience, blending expert-led lectures, practical lab sessions, real-world case studies, and engaging group discussions. These elements are strategically integrated to accelerate your Python proficiency, even if you’re starting with minimal scripting knowledge.
By the conclusion of this program, you will have not only honed your Python scripting skills but also gained mastery in manipulating data using prominent Python libraries and leveraging visualization techniques to communicate insights effectively.
Our holistic approach ensures that you not only grasp the fundamentals of Python but also develop the confidence to apply your newfound skills seamlessly in your professional endeavors. Get ready to embark on a transformative journey where you’ll not only learn Python but also harness its power to drive innovation and success in your career.
Applied Python for Data Science & Engineering Course Objectives
Under the guidance of experienced instructors, attendees will:
- Acquire essential Python scripting skills for creating and executing basic programs.
- Design and implement modules and classes effectively.
- Develop and run unit tests to ensure the reliability of your code.
- Employ benchmarks and profiling techniques to optimize program performance.
- Gain expertise in processing data in various formats, including XML, JSON, and CSV.
- Effectively manipulate arrays using NumPy.
- Explore the diverse subpackages within SciPy for advanced scientific computing.
- Master the use of Series and Dataframes with Pandas, a crucial skill for data analysis.
- Leverage Jupyter notebooks for ad hoc calculations, data visualization, and scenario analysis.
Prerequisites
- 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.
Audience
This course is tailored for the following professionals:
- Data Analysts
- Developers
- Engineers
- Individuals tasked with utilizing Python for data analytics tasks
Applied Python for Data Science & Engineering Outline
$2395.00
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4 Days Course |