Data Science with Python

This course equips you with the knowledge and skills to read, explore, and manipulate data, and then create and use successful models from the data gathered.

Course Duration: 4 days (full-time) 

Daytime Classes | Evening Classes | Virtual & Online Classes                                                        


You will learn to…

Import a variety of data formats into Python

Iteration and evaluation of Data with Python

Clean & pre-process data in preparation for analysis

Pre-process unstructured data for text-mining

Partitioning Data for Modelling and Modelling Techniques

Apply regression, clustering and classification in Python

About this course

Python is an open-source, free programming language and environment for statistical computing, data analysis, and graphics. Python is becoming commonly used by data scientists, statisticians, analysts who need to make sense of data. Well designed for effective data handling and storage facility. This course introduces delegates to Python environment, delegate will learn how to manipulate data, data exploration, data transformation, modelling, and effective interpretation of results. Also you will be able to build statistical models such as regression, clustering, classification and other modelling techniques.

4 Benefits of booking this course with us

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With a strong presence in all the main sites across of UK, Pairview dedicate all the efforts to deliver the most full superior learning experience. Our Education Centre classrooms are designed to provide a unique, inspiring and secure learning environment . Our experienced trainers take our delegates to the next level, supporting all their needs, giving them the skills-set to be ahead of the most in-demand tools of this field.



Enjoy a broad choice of courses/ classes and dates – choose from all available of dates and course events anywhere in the UK. Choose one of the Pairview’s site classrooms across of UK to have your training classes. Our classrooms are designed to leverage sophisticated training technology with LIVE virtual classes in order to give you the most live and superior learning experience.

With our virtual classes you can attend to all training sessions in any Pairview’s site classrooms. You will be LIVE in the session and you will be able to communicate easily in real time with your course instructor and classmates – ask questions, get clarification and contribute your insights – everything with live voice and image.

Online – via AnyWhere

Attend all the training sessions Online – via AnyWhere. Control an LIVE in-class computer using our own Pairview’s interface. You will be able to communicate easily in real time with your course instructor and classmates – ask questions, get clarification and contribute your insights – everything with live voice and image. Your instructor will be able to see exactly how you’re doing and can interactively support you at the moment just like in a classroom.

You Can be in your home or in the other part of the world. With this solution you can attend all the Training Courses online – via AnyWhere.

Avoid long journeys to attend your training sessions in some particular site, save your time and your money with this singular option.



“The facilitator is very knowledgeable with years of experience, the course delivery was exceptional.”
Anonymous, Course Feedback Form

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Course Content

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  • Module 1: Applied Machine Learning
    Statistical learning vs. Machine learning
    Iteration and evaluation
    Bias-Variance trade-off
  • Module 2: Introduction to Python
    Understand the basic and Advanced Concepts of Python
    Python language characteristics
    Python IDLE and execution Model
    PYTHON programs on UNIX and Windows platform
    Python Editors and IDEs
  • Module 3: Python Basics
    Buit-in Funtions
    Different kind of literals
    Math Operations and Expressions
    Writing to Screen
    String Formatting
    Command Line Parameters
    Flow Control
  • Module 4: Sequences and File Operations
    Text file I/O
    Opening a Text File
    The with Block
    Reading and writing a Text File
    Indexing and Slicing
    Iterating through a Sequence
    Functions for All Sequences
    Using enumerate()
    Operators and Keywords for Sequences
    The xrange() Function
    List Comprehensions
    Generator Expressions
    Dictionaries and Sets
  • Module 5: Create functions, sorting different elements and error handling techniques
    Function Parameters
    Global Variables
    Variable Scope
    Returning Values
    Sorting lists, functions, collections and dictionaries.
    Generic Handling and Handling Multiple Exceptions.
    Raising and Re-raising Exceptions
    Import Statement and Search Path Module
  • Module 6: Modules
    Understanding what is a Modules
    OS and SYS Modules
    Environment Variables
    Launching External Processes
    Paths, Directories, and Filenames
    Walking Directory Trees
    Dates and Times
  • Module 7: Pythonic Idioms
    Common Python Idioms
    Packing and Unpacking
    Lambda Functions
    List Comprehensions
    Generators vs Iterators
  • Module 8: Services Modules and Packages
    Module Zipped Archives
    Import Statement
    Pyc File I/O
    Module search Path
    Module Aliases
  • Module 9: Classes
    Introduction to Python Classes
    Defining Classes
    Instance Objects Methods and Attributes
    Class Data
    Statistic Methods
    Pseudo-private Variables
  • Module 10: Developer Tools
    Program Development
    Customizing pylint
    Unit Testing and Test Class
    Establishing Success or Failure
    Start-up and Clean-up
    Running Tests
    Python Debugger and Debug Mode
    Setting Breakpoints
  • Module 11: XML and JSON
    Normal Approaches to XML
    Use the right Module
    Creating, Parsing and Navigating a XML Document
    Advanced XPath
  • Module 12: iPython
    Features of iPython
    Tab Completion
    External Commands
  • Module 13: Popular Python Plugins
    Numpy extention
    Working and interacting with Numpy extension in Python environment
    Scipy Library
    Basic plotting using Matplotlib
    Introduction to Pandas in Python environment
  • Module 14: Python Imaging Library
    The PIL
    Supported Image File Types
    The Image Class
    Reading and Writing
    Creating Thumbnails
    Coordinate System
    Cropping and Pasting
    Rotating, Resizing, and Flipping
    Module 15: Deploying and using Models
Experience of a data Query language such as SQL or SAS, strong statistical background.

£1,980 per person, ex VAT

£1,683 per person, ex VAT