Python Training Courses

At our training institute, we offer Python training courses that cover everything from the fundamentals to advanced concepts, and prepare you for Python Institute certifications. Our courses are designed to teach you how to write Python programs, develop web applications, and work with data in Python. We offer a comprehensive curriculum that includes hands-on exercises, quizzes, and assignments to reinforce your learning. Our instructors are experts in Python and have extensive experience in teaching the language to students of all levels.

What sets us apart from other Python training providers is the flexibility we offer in terms of class formats. You can choose to attend our courses in-person, online or through self-paced learning options. Our courses are designed to accommodate the needs of working professionals and students alike, with flexible schedules that can be tailored to fit your busy lifestyle. We understand that everyone learns differently, which is why we offer multiple class formats to suit different learning styles.

By taking our Python training courses, you will not only gain a solid understanding of the language, but also develop practical skills that can be applied in real-world scenarios. Our courses are designed to be hands-on and interactive, allowing you to work on projects and apply the concepts you have learned in class. Our instructors provide personalized support and guidance throughout your learning journey, ensuring that you are well-prepared for Python Institute certifications and have the skills needed to succeed in your career.

Python Certification Training

Our fundamentals to advanced python training courses are based on the Python Institutes certifications objectives. Students completing these training courses will be able to pass the Python certification exams from entry-level to professional.

Description
Python Fundamentals (PCEP | Certified Entry-Level Python Programmer)
Python Intermediate (PCAP | Certified Associate in Python Programming)

Python Advanced (PCPP | Certified Professional in Python Programming 1)

Python Advanced (PCPP | Certified Professional in Python Programming 2)

 

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Python Specialist Training

With the growth of Data Science, Artificial Intelligence, and Machine Learning we have introduced courses that focus on the specific needs of professionals looking to gain additional skills in this area.

 

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Certified Entry-Level Python Programmer Training

The Certified Python Entry Level Programmer (PCEP) certification provides students with a solid understanding of the Python language and builds a solid foundation for more advanced Python training and certification.  Master Python sequences, understand the dynamic and strongly typed nature of Python and what this means for function design.

PCEP | Certified Entry-Level Python Programmer Certification

  • Basic Concepts
    • fundamental concepts: interpreting and the interpreter, compilation and the compiler, language elements, lexis, syntax and semantics, Python keywords, instructions, indenting
    • literals: Boolean, integer, floating-point numbers, scientific notation, strings
    • comments
    • the print() function
    • the input() function
    • numeral systems (binary, octal, decimal, hexadecimal)
    • numeric operators: ** * / % // + –
    • string operators: * +
    • assignments and shortcut operators
  • Data Types, Evaluations, and Basic I/O Operations
    • operators: unary and binary, priorities and binding
    • bitwise operators: ~ & ^ | << >>
    • Boolean operators: not and or
    • Boolean expressions
    • relational operators ( == != > >= < <= ), building complex Boolean expressions
    • accuracy of floating-point numbers
    • basic input and output operations using the input(), print(), int(), float(), str(), len() functions
    • formatting print() output with end= and sep= arguments
    • type casting
    • basic calculations
    • simple strings: constructing, assigning, indexing, slicing comparing, immutability
  • Flow Control – loops and conditional blocks (20%)
    • conditional statements: if, if-else, if-elif, if-elif-else
    • multiple conditional statements
    • the pass instruction
    • building loops: while, for, range(), in
    • iterating through sequences
    • expanding loops: while-else, for-else
    • nesting loops and conditional statements
    • controlling loop execution: break, continue
  • Data Collections – Lists, Tuples, and Dictionaries
    • simple lists: constructing vectors, indexing and slicing, the len() function
    • lists in detail: indexing, slicing, basic methods (append(), insert(), index()) and functions (len(), sorted(), etc.), del instruction, iterating lists with the for loop, initializing, in and not in operators, list comprehension, copying and cloning
    • lists in lists: matrices and cubes
    • tuples: indexing, slicing, building, immutability
    • tuples vs. lists: similarities and differences, lists inside tuples and tuples inside lists
    • dictionaries: building, indexing, adding and removing keys, iterating through dictionaries as well as their keys and values, checking key existence, keys(), items() and values() methods
    • strings in detail: ASCII, UNICODE, UTF-8, immutability, escaping using the \ character, quotes and apostrophes inside strings, multiline strings, copying vs. cloning, advanced slicing, string vs. string, string vs. non-string, basic string methods (upper(), lower(), isxxx(), capitalize(), split(), join(), etc.) and functions (len(), chr(), ord()), escape characters
  • Functions
    •  defining and invoking your own functions and generators
    •  return and yield keywords, returning results,
    •  the None keyword,
    •  recursion
    •  parameters vs. arguments,
    •  positional keyword and mixed argument passing,
    •  default parameter values
    •  converting generator objects into lists using the list() function
    •  name scopes, name hiding (shadowing), the global keyword

Certified Associate in Python Programming Training

The Python Certified Associate Programming certification builds on the foundation of the Python Fundamentals training for the certified Python Entry Level Programmer course by expanding on the basics of functions, flow control and sequences and provides a solid foundation for mastering object-orientated programming in Python.

PCAP | Certified Associate in Python Programming course objectives

  • Control and Evaluations
    • basic concepts: interpreting and the interpreter, compilation and the compiler, language elements, lexis, syntax and semantics, Python keywords, instructions, indenting
    • literals: Boolean, integer, floating-point numbers, scientific notation, strings
    • operators: unary and binary, priorities and binding
    • numeric operators: ** * / % // + –
    • bitwise operators: ~ & ^ | << >>
    • string operators: * +
    • Boolean operators: not and or
    • relational operators ( == != > >= < <= ), building complex Boolean expressions
    • assignments and shortcut operators
    • accuracy of floating-point numbers
    • basic input and output: input(), print(), int(), float(), str() functions
    • formatting print() output with end= and sep= arguments
    • conditional statements: if, if-else, if-elif, if-elif-else
    • the pass instruction
    • simple lists: constructing vectors, indexing, and slicing, the len() function
    • simple strings: constructing, assigning, indexing, slicing comparing, immutability
    • building loops: while, for, range(), in, iterating through sequences
    • expanding loops: while-else, for-else, nesting loops, and conditional statements
    • controlling loop execution: break, continue
  • Data Aggregates
    • strings in detail: ASCII, UNICODE, UTF-8, immutability, escaping using the \ character, quotes and apostrophes inside strings, multiline strings, copying vs. cloning, advanced slicing, string vs. string, string vs. non-string, basic string methods (upper(), lower(), isxxx(), capitalize(), split(), join(), etc.) and functions (len(), chr(), ord()), escape characters
    • lists in detail: indexing, slicing, basic methods (append(), insert(), index()) and functions (len(), sorted(), etc.), del instruction, iterating lists with the for loop, initializing, in and not in operators, list comprehension, copying and cloning
    • lists in lists: matrices and cubes
    • tuples: indexing, slicing, building, immutability
    • tuples vs. lists: similarities and differences, lists inside tuples and tuples inside lists
    • dictionaries: building, indexing, adding and removing keys, iterating through dictionaries as well as their keys and values, checking key existence, keys(), items() and values() methods
  • Functions and Modules (25%)
    • defining and invoking your own functions and generators
    • return and yield keywords, returning results, the None keyword, recursion
    • parameters vs. arguments, positional keyword and mixed argument passing, default parameter values
    • converting generator objects into lists using the list() function
    • name scopes, name hiding (shadowing), the global keyword
    • lambda functions, defining and using
    • map(), filter(), reduce(), reversed(), sorted() functions and the sort() method
    • the if operator
    • import directives, qualifying entities with module names, initializing modules
    • writing and using modules, the __name__ variable
    • pyc file creation and usage
    • constructing and distributing packages, packages vs. directories, the role of the __init__.py file
    • hiding module entities
    • Python hashbangs, using multiline strings as module documentation
  • Classes, Objects, and Exceptions
    • defining your own classes, superclasses, subclasses, inheritance, searching for missing class components, creating objects
    • class attributes: class variables and instance variables, defining, adding, and removing attributes, explicit constructor invocation
    • class methods: defining and using, the self parameter meaning and usage
    • inheritance and overriding, finding class/object components
    • single inheritance vs. multiple inheritance
    • name mangling
    • invoking methods, passing and using the self argument/parameter
    • the __init__ method
    • the role of the __str__ method
    • introspection: __dict__, __name__, __module__, __bases__ properties, examining class/object structure
    • writing and using constructors
    • hasattr(), type(), issubclass(), isinstance(), super() functions
    • using predefined exceptions and defining your own ones
    • the try-except-else-finally block, the raise statement, the except-as variant
    • exceptions hierarchy, assigning more than one exception to one except branch
    • adding your own exceptions to an existing hierarchy
    • assertions
    • the anatomy of an exception object
    • input/output basics: opening files with the open() function, stream objects, binary vs. text files, newline character translation, reading and writing files, bytearray objects
    • read(), readinto(), readline(), write(), close() methods

Certified Professional in Python Programming 1 Training

 

The Python Certified Professional Python Programmer Level 1 (PCPP1) covers advanced object-oriented programming, network and GUI programming as well as best practices when it comes to writing code in a Pythonic style. Become a professional Python programmer by getting PCPP certified.

PCPP-32-1: Certified Professional in Python Programming 1

  • File Processing and Communicating with a Program’s Environment
    • Processing different kinds of files
      • sqlite3 – interacting with SQLite databases
      • xml – creating and processing XML files
      • csv – CSV file reading and writing
      • logging – basics logging facility for Python
      • configparser – configuration file parser
    •  Communicating with a program’s environment:
      • os – interacting with the operating system,
      • datetime – manipulating with dates and time
      • io – working with streams,
      • time – time access and conversions
  • GUI Programming
    • What is GUI and where it comes from
    • Constructing a GUI – basic blocks and conventions
    • Event-driven programming
    • Currently used GUI environments and toolkits
    • tkinter — Python interface to Tcl/Tk
      • tkinter’s application life cycle
      • Widgets, windows and events
      • Sample applications
      • pygame – a simple way of developing multimedia applications
  • Python Enhancement Proposals
    • What is PEP?
    • Coding conventions – not only style and naming
    • PEP 20 – The Zen of Python: a collection of principles that influences the design of Python code
    • PEP 8 – Style Guide for Python Code: coding conventions for code comprising the standard library in the main Python distribution
    • PEP 257 – Docstring Conventions: what is docstring and some semantics as well as conventions associated with them
    • A tour of important PEPs
  • Python Network Programming
    • Python Socket Module
      • Introduction to sockets
      • Server Socket Methods
      • Client socket methods
      • General socket methods
      • Client-Server vs. Peer-to-peer
      • Other Internet nodules
  • Advanced Perspective of Classes and Object-Oriented Programming in Python
    • Classes, Instances, Attributes, Methods
    • Working with class and instance data
    • Copying object data using shallow and deep operations
    • Inheritance and Polymorphism
    • Different faces of Python methods: static and class methods
    • Abstract classes vs. method overloading
    • Composition vs. Inheritance – two ways to the same destination
    • Implementing Core Syntax
    • Subclassing built-ins
    • Attribute Encapsulation
    • Advanced techniques of creating and serving exceptions
    • Serialization of Python objects using the pickle module
    • Making Python object persistent using the shelve module
    • Metaprograming
      • Function decorators
      • Class decorators
      • Metaclasses

Certified Professional in Python Programming 2 Training

 

The 2nd certification for advanced Python programming from the Python Institute cover the best practice for creating and distributing your Python code, interprocess communication and design patterns. It also provided an introduction to the core data science libraries and tools in Python. The certification is a great foundation to launch your specialisation in data science and Python

PCPP-2: Certified Professional in Python Programming 2 Certification

  • Creating and Distributing Packages
    • Using pip
    • Basic directory structure
    • The setup.py file
    • Sharing, storing, and installing packages
    • Documentation
    • License
    • Testing principles and techniques
      • unittest – Unit testing framework
      • Pytest – framework to write tests
  • Math, Science, and Engineering Tools
    • math – a basic tool for elementary evaluations
    • NumPy – fundamental package for scientific computing
    • SciPy – an ecosystem for mathematics, science, and engineering
    • Matplotlib – 2D plotting library producing publication quality figures
    • Pandas – a library providing high-performance and data analysis tools
    • SciKit-image – a collection of algorithms for image processing
  • Design Patterns
    • Object-oriented design principles and the concept of design patterns
    • The Singleton Design Pattern
    • The Factory Pattern
    • The Façade Pattern
    • The Proxy Pattern
    • The Observer Pattern
    • The Command Pattern
    • The Template Method Pattern
    • Model-View-Controller
    • The State Design Pattern
  • Interprocess Communication
    • multiprocessing — Process-based parallelism
    • threading — Thread-based parallelism
    • subprocess — Subprocess management
    • Multiprocess synchronisation
      • queue — A synchronized queue class
      • socket — Low-level networking interface
      • mmap — Memory-mapped file support
  • Python-MySQL Database Access
    • Relational databases – fundamental principles and how to work with them
    • MySQL vs. rest of the world
    • CRUD Application
      • db connection
      • db create
      • db insert
      • db read
      • db update
      • db delete

Our Clients

Absa Bank Dimension Data Teraco Discovery Health South African Revenue Service First National Bank Allan Grey multichoice CSIR Standard Bank University of Johannesburg MTN Mr Price

Python for Data Science Training

Unleash the power of machine learning and artificial intelligence with the key python libraries and projects ones needs to know to become a data science master. Conquer data visiaulisation with Pandas,  Matplotlib and Seaborn. Quickly analyse and present data with Jupyter Notebooks and learn how to use the key algorithms of scikit-learn.

  • Introduction & Review of Python Syntax - Quick introduction to Python and revision of the fundamentals of Python Programming
  • Jupyter Notebooks - Learn how to use Jupyter Notebooks for interactive data science & scientific computing
  • Numpy - Master the basics of data analysis in Python with Numpy. Expand your skill set by learning scientific computing.
  • Pandas - Learn how to use the industry-standard pandas library to import, build, and manipulate DataFrames. Learn how to tidy, rearrange, and restructure your data using versatile pandas DataFrames.
  • Visualisations - Level up your data science skills by creating visualizations using matplotlib and manipulating data frames with Pandas. master complex data visualization techniques using Matplotlib and Seaborn and create versatile and interactive data visualizations using Bokeh.
  • Machine Learning 
    • Supervised learning with scikit-learn: Learn how to build and tune predictive models with supervised learning and understand how to evaluate their performance on unseen data. Learn how to build a model to automatically classify items.
    • Unsupervised learning with scikit-learn: Learn how to cluster, transform, visualize, and extract insights from unlabeled datasets using scikit-learn and scipy.
    • Neural Networks using Keras 2.0:  Learn the fundamentals of neural networks and how to build deep learning models.
    • Network Analysis - Master the skills to analyze, visualize, and make sense of networks using the NetworkX library.
  • Working with databases & text processing - Learn to import data into Python from various sources, such as Excel, SQL, SAS and from the web. Master the basics of querying tables in relational databases such as MySQL, Oracle, SQL Server, and PostgreSQL.

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Ferndale,

2194 South Africa
Tel: +2711-781 8014
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