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Python for Data Science and Data Analysis Bootcamp

Batch Price From £500 (approx. $623 USD) View Dates & Prices Python for Data Science and Data Analysis Bootcamp
Total Duration: 20 Hours
Course level: Beginner
Delivery Method: Instructor led online training
Certification: Certificate of Completion will be provided after completing the course

Course Overview

This Bootcamp is designed for beginners who wish to become a software developer by using Python, which is a widely used general-purpose, high-level programming language. It is an online classroom-based course that covers the essential topics to start programming with Python.

In this Bootcamp, you will also learn the concepts and tools to utilize in a data science project. You will be taught a practical approach to developing an end-to-end data science project cycle right from extracting data from different types of sources to exposing your machine learning model that can be consumed in a real-world data solution. We will teach an industry-standard approach to data science projects using Python.

The students will learn to use various standard libraries in the Python ecosystem such as Pandas, NumPy, Matplotlib, Scikit-Learn, Flask to tackle different stages of a data science project such as extracting data, cleaning and processing data, building and evaluating machine learning model.

After the completion of this Bootcamp, participants will have a solid foundation to handle any data science project and have the knowledge to apply various Python libraries to create a data science solution.

Requirements

No existing knowledge of Python programming is required. You should have basic computing knowledge.

Course Dates, Prices & Enrolment

All Training Physical Classes Virtual Classes
Time Zone:
There is no date for this course at this moment. Please complete the BOOKING REQUEST FORM below or come back to this page again later.

Course Content

  1. Python Modes
    • Normal
    • Interactive
  2. Built-in Functions
    • Help utility
    • Keywords
    • Symbols
  3. Variables
    • Data type
    • Identifier
    • Assignment operator
    • Value
  4. Python Statements
    • Carriage returns
    • Colon :
    • Indentation
  5. Keyboard Input
    • Built-in Function
    • Prompt
  6. Selection Statements
    • Boolean expressions and variables
    • The if Statement
    • Nested-if Statements
  7. Repetition Statements (Loops)
    • The while Statement
    • The for Statement
    • Nested-for Statements
  8. Python Containers
    • Tuple
    • List
    • Set
    • Dictionary
  9. File Input and Output
    • File Object
    • High-Level File I/O
  10. Python for Data Science - Introduction
  11. Setting up Working Environment
  12. Extracting Data from multiple sources
  13. Data Cleansing and pre processing
  14. Exploring and Processing Data
  15. Building and Evaluating Predictive Models

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