Applied Data Science With Python And Jupyter

Our Applied Data Science With Python And Jupyter training course will cover the following Modules:

Module 1: Jupyter Fundamentals

• Basic Functionality and Features
• Our First Analysis - The Boston Housing Dataset

Module 2: Data Cleaning and Advanced Machine Learning

• Preparing to Train a Predictive Model
• Training Classification Models

Module 3: Web Scraping and Interactive Visualisations

• Scraping Web Page Data

Our Applied Data Science With Python And Jupyter training course will benefit several individuals and organisations including but not limited to:

• Data Analysts
• Business Analysts
• Data Scientists
• Data Engineers
• Software Developers
• Researchers
• IT Professionals
• Decision Makers
• Any Data Enthusiast

Our Applied Data Science With Python And Jupyter training course contains the following:

• 1-day instructor-led training course
• One-on-one after course instructor coaching
• Pre-reading
• Course Manual
• Quizzes
• Exercises

Our Applied Data Science With Python And Jupyter training course requires attendees to have:

• Knowledge of programming fundamentals and some experience with Python, including Python libraries, Pandas, Matplotlib, and scikit-learn.

There is no recommended reading for our Applied Data Science With Python And Jupyter training course.

Applied Data Science With Python And Jupyter Exam:

• Format: Multiple Choice
• Questions: 40
• Pass Mark: 70%

Attendees may enjoy our three-day Introduction To Python training course.

Our three-day Introduction To Python training course will provide a foundation for learning and understanding the Python programming language. Python is a versatile and widely used programming language known for its simplicity, readability, and a large number of libraries and frameworks that make it suitable for various applications. We will teach you how to use Python’s features, standard library modules, and third-party software packages.

Our Applied Data Science With Python And Jupyter training course offers several benefits to individuals and organisations including but not limited to:

• In-Demand Skill Set: Data science is a rapidly growing field, and proficiency in Python and Jupyter is highly valued by employers.
• Practical Data Analysis Skills: The training focuses on practical application, equipping you with the skills needed to manipulate, analyse, and visualise data using Python and Jupyter.
• Industry-Relevant Techniques: The training covers a range of data science techniques, including data manipulation, data visualisation, machine learning, and model evaluation.
• Hands-On Experience: The training typically includes hands-on exercises and projects, providing you with opportunities to apply the concepts and techniques learned.
• Flexibility and Reproducibility: Python and Jupyter offer flexibility and reproducibility in data analysis workflows.
• Enhanced Problem-Solving Skills: Data science involves solving complex problems and extracting meaningful insights from data.
• Data-Driven Decision Making: Data science skills empower you to make informed decisions based on data rather than relying solely on intuition or guesswork.
• Career Advancement Opportunities: Proficiency in Applied Data Science with Python and Jupyter can lead to career advancement opportunities, whether you are seeking a new job, aiming for a promotion within your current organisation, or considering entrepreneurship in the data science domain.
• Networking and Community: Python and Jupyter have a large and active community of data scientists and developers.
• Lifelong Learning: Data science is a rapidly evolving field, and learning Applied Data Science with Python and Jupyter is a stepping stone for continuous learning.