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Python Data Wrangling training course

Master the art of data Wrangling with our Python Data Wrangling Training Course. Dive into hands-on session that guide you through essential techniques for clean, transform, extract and repair Data using Python.

JBI training course London UK

"Our tailored course provided a well rounded introduction and also covered some intermediate level topics that we needed to know.  Helps data analysts with task related to big data as well. 

Brian Leek, Data Analyst, May 2023

Public Courses

02/01/25 - 3 days
£1995 +VAT
13/02/25 - 3 days
£1995 +VAT
27/03/25 - 3 days
£1995 +VAT

Customised Courses

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JBI training course London UK

  • Data Wrangling with Python Training: 
  • Introduction to Data Wrangling with Python 
  • Introduction to Python programming language
  • Overview of the Pandas library for data manipulation & analysis
  • Learn how to Read & writing various data formats (CSV, Excel, SQL)
  • Exploratory Data Analysis (EDA): Descriptive statistics for understanding dataset characteristics.
  • Introduction to Regular Expressions: Pattern matching for data cleaning.
  • Learn to write scripts for automating repetitive data wrangling tasks.
  • Applying learned skills to real-world projects
  • Introduction to version control systems (e.g., Git),managing code changes.
  • Learn to clean, transfer and scrap data using Python and its related tools

 Introduction to Data Wrangling:  

  • Understanding the importance of data wrangling in the data science workflow
  • Common challenges & issues in raw datasets

Python Basics for Data Wrangling:

  • Introduction to Python programming language.
  • Data types, variables, and basic operations.
  • Working with Pandas:
  • Overview of the Pandas library for data manipulation and analysis.
  • Reading and writing various data formats (CSV, Excel, SQL).
  • DataFrame creation and manipulation.

Data Cleaning Techniques:

  • Identifying and handling missing data.
  • Removing duplicates.
  • Data type conversion and normalization.
  • Exploratory Data Analysis (EDA):
  • Descriptive statistics for understanding dataset characteristics.
  • Visualizations using libraries like Matplotlib and Seaborn.

Data Transformation:

  • Reshaping and pivoting data.
  • Merging and joining datasets.

Handling Time Series Data:

  • Working with time-based data using Pandas.
  • Resampling and frequency conversion.

Data Wrangling with NumPy:

  • Introduction to NumPy for numerical operations.
  • Working with arrays and matrices.
  • Introduction to Regular Expressions:
  • Pattern matching for text data cleaning.
  • Using regular expressions for data extraction.

Data Wrangling Best Practices:

  • Writing modular and reusable code.
  • Handling large datasets efficiently.
  • Error handling and debugging techniques.
  • Real-world Case Studies:
  • Applying data wrangling skills to real-world datasets.
  • Solving practical challenges in diverse domains.

Integration with Other Tools:

  • Integrating data wrangling into the broader data science ecosystem.
  • Collaboration with databases and big data frameworks.

Version Control for Data Wrangling Scripts:

  • Introduction to version control systems (e.g., Git) for managing code changes.
  • Best practices for collaborative data wrangling projects.
  • Automation and Scripting:
  • Writing scripts for automating repetitive data wrangling tasks.
  • Building data pipelines for efficient workflows.

Advanced Topics (Optional):

  • Advanced Pandas features.
  • Custom functions and transformations.
  • Introduction to machine learning data preparation.

Hands-on Projects:

  • Applying learned skills to real-world projects.
  • Feedback and code review for improvement.
  • Final Project and Certification:
  • Capstone project to showcase comprehensive data wrangling skills.
  • Certification upon successful completion of the course. 

 

JBI training course London UK

This Data Wrangling Training course is designed for aspiring data professionals, analysts, and scientists seeking to master the essential skill of data wrangling using Python. Whether you're a beginner looking to build a strong foundation or an experienced data practitioner, this course caters to a diverse audience. Specifically, it is ideal for:

  • Data Enthusiasts: Individuals with a passion for working with data who want to learn how to effectively clean, transform, and analyze datasets.

  • Data Analysts: Professionals involved in extracting insights from data who wish to streamline their data preparation processes.

  • Data Scientists: Those working in or aspiring to enter the field of data science, looking to bolster their skills in handling diverse and complex datasets.

  • Business Analysts: Professionals responsible for extracting meaningful business insights from data & wanting to optimize their data manipulation workflows.

  • Researchers: Academics and researchers who deal with data for their studies and want to acquire practical skills in preparing and analyzing datasets.

  • IT Professionals: Developers and IT specialists interested in expanding their Python programming skills to include data manipulation for a more comprehensive understanding of data workflows.

  • Anyone Transitioning to Data Roles: Individuals transitioning from other fields to data-related roles, seeking a practical and hands-on introduction to data wrangling with Python.


5 star

4.8 out of 5 average

"Our tailored course provided a well rounded introduction and also covered some intermediate level topics that we needed to know.  Helps data analysts with task related to big data as well. 

Brian Leek, Data Analyst, May 2023



“JBI  did a great job of customizing their syllabus to suit our business  needs and also bringing our team up to speed on the current best practices. very impressive”

Brian F, Team Lead, RBS, Data Analysis Course, 20 April 2022

 

 

JBI training course London UK

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                             Data Wrangling With Python Training 

Unlock the full potential of data with our Data Wrangling with Python course. Ideal for data enthusiasts, analysts, and scientists, this program covers essential Python skills for cleaning, transforming, and analyzing datasets. Whether you're a beginner or an experienced professional, you'll gain hands-on experience with Pandas, NumPy, and other tools.

Master data cleaning techniques, exploratory data analysis, and real-world applications. Elevate your data wrangling proficiency and advance your career in this dynamic and crucial field. Join us for a transformative learning experience in the world of data.

By the end of the course, participants will have gained the knowledge and practical experience needed to confidently wrangle diverse datasets, setting the stage for successful data-driven decision-making and analysis in their respective domains.

Join us on this learning journey and unlock the power of Python for effective data manipulation and preparation.

What prerequisites are required for this course?

Basic knowledge of Python programming is recommended, but the course is designed to accommodate beginners as well. Familiarity with fundamental data concepts is beneficial.

Do I need prior experience in data science or analysis?

No, the course caters to individuals with varying levels of experience. Whether you're new to data or seeking to enhance your skills, the content is structured to accommodate diverse backgrounds.

What tools and libraries will be covered in the course?

The course primarily focuses on Python for data wrangling, with an emphasis on Pandas and NumPy. Additionally, you'll explore Matplotlib and Seaborn for data visualization.

Can I access the course materials after completion?

Yes, participants will have access to course materials, including lectures, code examples, and additional resources, allowing continued learning and reference even after completing the course.

Are there hands-on projects in the course?

Absolutely! The course includes hands-on projects that allow you to apply your newfound skills to real-world scenarios, reinforcing the concepts learned during the lectures.

Is there a certification upon completion of the course?

Yes, a certification of completion will be awarded to participants who successfully finish the course, demonstrating their proficiency in data wrangling with Python.

How much time should I dedicate to the course each week?

The course is designed to be flexible, allowing participants to learn at their own pace. On average, dedicating a few hours per week should be sufficient to cover the material within the recommended timeframe.

Will there be opportunities for interaction and collaboration?

Yes, the course encourages interaction through discussion forums and collaborative projects. Participants can engage with instructors and peers to enhance their learning experience.

Can I use the skills learned in this course in my professional work?

Absolutely. The practical nature of the course ensures that participants can directly apply the acquired skills to their professional roles, making it relevant and beneficial in various industries.

Is technical support provided during the course?

Yes, technical support will be available to assist participants with any issues related to the course platform, materials, or exercises. Our goal is to ensure a smooth learning experience for all participants.

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