More dates

Payment plans

How does it work?

  • Reserve your order today and pay over time in regular, automatic payments.
  • You’ll receive your tickets and items once the final payment is complete.
  • No credit checks or third-party accounts - just simple, secure, automatic payments using your saved card.

Python Essentials for Data Science: 1 Day Session in Christchurch

Share
 · 
Hazeldean Road
Christchurch, New Zealand
Add to calendar
 

Description

About This Course

  • Duration: 1 Full Day (8 Hours)

  • Delivery Mode: Classroom (In-Person)

  • Language: English

  • Credits: 8 PDUs / Training Hours

  • Certification: Course Completion Certificate

  • Refreshments: Lunch, snacks, and beverages will be provided


If you would like weekend training sessions, kindly reach out to us at info@mangates.com for availability and scheduling.

Course Overview

The Python for Data Science course provides the essential skills to analyze, visualize, and interpret data using Python. You’ll learn to use popular libraries like Pandas, NumPy, Matplotlib, and Seaborn to explore datasets and uncover insights. Designed for aspiring data scientists and analysts, this course bridges core programming with data-driven decision-making — empowering you to start your journey in the world of data science.


Learning Objectives

By the end of this course, you will:

  • Use Python libraries to load, explore, and manipulate data

  • Apply data cleaning techniques to prepare data for analysis

  • Create visualizations to convey patterns and insights

  • Understand the basics of machine learning workflows

  • Perform data-driven decision-making with confidence

  • Start your journey toward becoming a skilled data analyst or scientist


Target Audience

Aspiring data scientists, analysts, developers, and students.


Why is it the Right Fit for You?

This course is designed for anyone ready to explore the world of data science using Python, regardless of prior experience. With expert guidance and real-world datasets, you’ll learn to make sense of data and present your findings visually. Our hands-on approach ensures you don’t just learn theory, but also apply it through practical exercises. Plus, Python is the most popular language in data science — learning it unlocks opportunities in AI, analytics, automation, and more.


©2026 Mangates Tech Solutions Pvt Ltd. This content is protected by copyright law. Copy or Reproduction without permission is prohibited.

Want to build a data-driven culture within your team?

We offer customizable in-house Python for Data Science training tailored to your organization's goals and data challenges. Looking to upskill your workforce in data handling and analysis? Let us design a program that fits your needs.

📧 Contact us today to schedule a customized in-house session: corporate@mangates.com

0 / 5

Gallery

Agenda

  • Module 1: Introduction to Python for Data Science

    • Why Python is essential for data science • Setting up Jupyter Notebook or VS Code • Overview of data science workflow • Activity

  • Module 2: Working with Data using Pandas

    • Introduction to DataFrames and Series • Reading and writing CSV, Excel files • Data exploration and basic stats • Activity

  • Module 3: Numerical Computing with NumPy

    • Understanding arrays and vectorized operations • Array creation, indexing, reshaping • Using NumPy for basic calculations • Case Study

  • Module 4: Data Cleaning Essentials

    • Handling missing data and duplicates • Data type conversions and string operations • Filtering, sorting, and transforming data • Activity

  • Module 5: Data Visualization with Matplotlib

    • Plotting line, bar, scatter, histogram charts • Customizing styles and labels • Creating multiple plots in a figure • Activity

  • Module 6: Advanced Visualization with Seaborn

    • Heatmaps, pair plots, categorical plots • Using themes and palettes • Visualizing data distributions • Activity

  • Module 7: Introduction to Machine Learning Concepts

    • What is machine learning? • Basics of supervised vs unsupervised learning • Using scikit-learn for simple models • Case Study

  • Module 8: Mini Data Project

    • Choose a dataset and perform analysis • Clean, analyze, visualize, and present findings • Share insights and interpretations • Activity

FAQs

  • Do I need to know Python before attending?


    It’s helpful but not required — basic concepts will be introduced.

  • Do I need any specific software installed?


    Yes, instructions to set up Python and Jupyter will be shared.

  • Will we work with real datasets?


    Yes, you’ll explore and visualize real-world data during the course.

  • Does this course cover machine learning in depth?

    No, only an introduction is covered, but it sets a foundation for further learning.

  • Is this course suitable for career changers?


    Absolutely, it's ideal for those moving into data or tech roles.

  • Do I need a strong math background?


    Basic understanding is useful, but not mandatory for this beginner-level course.

  • Will I receive support after the course?


    Yes, you can reach out with post-session questions for support.

  • Is there a certificate provided?


    Yes, you'll receive a course completion certificate.

  • Can this be tailored for corporate training?


    Yes, we offer fully customized sessions based on your team’s needs.

Powered by

Tickets for good, not greed Humanitix dedicates 100% of profits from booking fees to charity

Get tickets

Get tickets

Get tickets

Get tickets

Hazeldean Road
Christchurch, New Zealand
Host icon
Hosted by Mangates

More events from this host