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

Accredited Certificate from LearnDrive | Instant Access | 02 Courses Bundle

Summary

Price
£14.99 inc VAT
Study method
Online, On Demand
Duration
3.7 hours · Self-paced
Qualification
No formal qualification
Certificates
  • Accredited Certificate from LearnDrive - Free
  • Reed Courses Certificate of Completion - Free
  • Learndrive Special Bundle Certificate - £7
Additional info
  • Tutor is available to students
1 student purchased this course

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Overview

Dive into Data Science & Python with our Level 3 Diploma, tailored for aspiring data analysts. Master Python programming, data handling, and visualization techniques essential for data science. Transform your analytical skills and become proficient in Python and data science tools to tackle real-world data challenges.

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.

Courses Included:

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

Accreditation:

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

Certificates

Accredited Certificate from LearnDrive

Digital certificate - Included

Reed Courses Certificate of Completion

Digital certificate - Included

Will be downloadable when all lectures have been completed.

Learndrive Special Bundle Certificate

Digital certificate - £7

Curriculum

3
sections
27
lectures
3h 44m
total

    • 1: Python: Introduction to Python 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: Claim Your Free Accredited 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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Legal information

This course is advertised on Reed.co.uk by the Course Provider, whose terms and conditions apply. Purchases are made directly from the Course Provider, and as such, content and materials are supplied by the Course Provider directly. Reed is acting as agent and not reseller in relation to this course. Reed's only responsibility is to facilitate your payment for the course. It is your responsibility to review and agree to the Course Provider's terms and conditions and satisfy yourself as to the suitability of the course you intend to purchase. Reed will not have any responsibility for the content of the course and/or associated materials.

FAQs

Study method describes the format in which the course will be delivered. At Reed Courses, courses are delivered in a number of ways, including online courses, where the course content can be accessed online remotely, and classroom courses, where courses are delivered in person at a classroom venue.

CPD stands for Continuing Professional Development. If you work in certain professions or for certain companies, your employer may require you to complete a number of CPD hours or points, per year. You can find a range of CPD courses on Reed Courses, many of which can be completed online.

A regulated qualification is delivered by a learning institution which is regulated by a government body. In England, the government body which regulates courses is Ofqual. Ofqual regulated qualifications sit on the Regulated Qualifications Framework (RQF), which can help students understand how different qualifications in different fields compare to each other. The framework also helps students to understand what qualifications they need to progress towards a higher learning goal, such as a university degree or equivalent higher education award.

An endorsed course is a skills based course which has been checked over and approved by an independent awarding body. Endorsed courses are not regulated so do not result in a qualification - however, the student can usually purchase a certificate showing the awarding body's logo if they wish. Certain awarding bodies - such as Quality Licence Scheme and TQUK - have developed endorsement schemes as a way to help students select the best skills based courses for them.
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Similar subjects: Python, Data science, Coding, IT
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