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Level 3 Python Programming with Data Science & Data Analytics for Data Analysts
Learndrive

Python Strings | Python Dictionary | Python Loop | Python OOP | Numpy Package | Pandas | Matplotlib

Summary

Price
£19 inc VAT
Study method
Online, On Demand
Duration
3.7 hours · Self-paced
Qualification
No formal qualification
Certificates
  • Reed Courses Certificate of Completion - Free
Additional info
  • Tutor is available to students

6 students purchased this course

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Overview

Why Study This Course?

  • The UK digital sector continues to expand rapidly, with Python consistently ranked among the most in-demand programming skills for data-driven roles.

  • Employers across finance, healthcare and technology actively seek professionals proficient in Python for data analytics and automation.

  • Python expertise opens doors to high-growth careers in data science, business intelligence and advanced analytics.

Key Performance Metrics:

  • Utilize Python for diverse Data Science applications.
  • Implement effective Python string manipulation techniques.
  • Master Python casting and input for Data Science.
  • Manipulate data using Python dictionaries efficiently.
  • Control data flow with Python loops in Data Science contexts.

Opportunities in the UK Job Market

  1. Data Analyst – £30,000–£45,000 per annum
    Use Python to clean, analyse and visualise business data.

  2. Junior Data Scientist – £35,000–£55,000 per annum
    Apply Python, Numpy and Pandas to build predictive models.

  3. Business Intelligence Analyst – £32,000–£50,000 per annum
    Leverage Python and Matplotlib to generate strategic insights.

Courses Included:

  • Course 01: Certificate in Python Fundamentals
  • Course 02: Data Science and Data Analytics

Accreditation:

Level 3 Python Programming with Data Science Course is CPDQE accredited, which serves as an impactful mechanism for skill enhancement.

Certificates

Reed Courses Certificate of Completion

Digital certificate - Included

Will be downloadable when all lectures have been completed.

Curriculum

4
sections
28
lectures
3h 45m
total
    • 1: Python: Introduction to Python Preview 02:40
    • 2: Python: Working with Data Types 10:08
    • 3: Python: Python Strings 11:16
    • 4: Care for a Feedback 01:00
    • 5: Python: Python List 09:28
    • 6: Python: Python casting and Input 07:07
    • 7: Way to GO! 00:11
    • 8: Python: Python Dictionary 09:53
    • 9: Python: Python Date and Time 10:29
    • 10: Python: Python Loop Part 1 09:25
    • 11: Python: Python Loop Part 2 05:40
    • 12: Python: Python While Loop 06:12
    • 13: Python: Creating a Function 08:19
    • 14: Python: Python OOP Part 1 07:31
    • 15: Python: Python OOP Part 2 07:20
    • 16: Python: Python Advanced OOP Part1 12:49
    • 17: Python: Python Advanced OOP Part 2 07:54
    • 18: Python: Error handling 10:03
    • 19: Python: Python file handling 05:54
    • 20: Python: Python modules 03:31
    • 21: Data Science: Introduction to Data Science 02:59
    • 22: Data Science: Data Science Environment setup 10:15
    • 23: Data Science: Working with the Numpy package 15:46
    • 24: Data Science: Working with Pandas Data science package 19:11
    • 25: Data Science: Working with Matplotlib Data Science package part – 1 16:26
    • 26: Data Science: Working with Matplotlib Data Science part – 2 11:01
    • 27: Final Exam 01:00
    • 28: Order Your CPDQE Certificate 01:00

Course media

Description

Key Lesson Snippets:

➥ Working with Data Types in Data Science & Python
Explore fundamental and complex data types in Python. Learn how to effectively use these types in data analysis, ensuring a strong foundation for advanced data science tasks.

➥ Python Strings for Data Science
Delve into string operations and methods crucial for data cleaning and preparation in Python. Tailored for data science needs, this module enhances your ability to manipulate textual data efficiently.

➥ Python Casting and Input for Data Science
Learn how to convert data types and handle user input, a vital skill for creating interactive data science applications and preprocessing data for analysis.

➥ Python Dictionary for Data Science Applications
Master the use of dictionaries for storing and accessing data quickly and efficiently, a key technique in managing large datasets in Python.

➥ Python Loop Techniques in Data Science
Gain expertise in using loops to automate data processes, from simple data aggregation to complex data transformations, essential for robust data analysis.

➥ Error Handling in Python for Data Science
Understand how to manage and debug Python code by handling exceptions, crucial for maintaining the reliability and accuracy of data science models.

➥ Python File Handling for Data Science
Acquire skills in reading and writing files in Python, enabling you to handle various data formats and perform data persistence essential for any data science project.

➥ Utilizing Python Modules in Data Science
Explore popular Python modules and learn how to integrate them into your data science projects to extend functionality and improve efficiency.

➥ Data Science Environment Setup with Python
Set up a productive environment for data science, including essential Python packages and tools, to streamline your workflow and enhance productivity.

➥ Working with the Numpy Package for Data Science
Understand the power of Numpy for numerical operations in Python. This module covers array manipulations, matrix operations, and statistical calculations.

➥ Working with Pandas Data Science Package
Learn to manipulate data using Pandas, focusing on data frames for data cleaning, analysis, and visualization—key for any data-driven insights.

➥ Working with Matplotlib Data Science Package
Master data visualization with Matplotlib. Create plots and charts to communicate data insights visually, an indispensable skill in data analysis and presentation.

Career path

  • Data analyst
  • Data Scientist
  • Data Analytics Consultant
  • Data science intern
  • Python Data Scientist
  • Python Developer
  • Python Data Analyst

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FAQs

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