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Advanced Python Programming
Python is a high-level, general-purpose programming language. Its design philosophy emphasizes code readability with the use of significant indentation.
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COURSE OVERVIEW

Python is a high-level, general-purpose programming language. Its design philosophy emphasizes code readability with the use of significant indentation.

Python is dynamically-typed and garbage-collected. It supports multiple programming paradigms, including structured, object-oriented and functional programming.

Infoclub LTD brings you the latest frameworks and paradigms currently being used by Python Developers all over the world.

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PYTHON COURSE MODULES

PYTHON (P1) FUNDAMENTALS

Candidates who have no prior knowledge of Python would need to undergo these topics before looking at more advanced ones below:

Algorithms and problem solving on computers. Variables and data types. Simple operations. Working in Anaconda, Spyder and IDLE environments. IF statements. Loops with for and while. Strings. Built-in functions and modular programming. Lists, tuples, Dictionaries. Read/write to files. Plotting graphs with matplotlib. GUI functions in Python. Using Numpy library. Using APIs to retrieve data.

ADVANCED DATA STRUCTURES (A1)

• Object oriented Programming concepts
• Create Classes in Python
• Class Inheritance.
• Operator and function overloading
• More on lists, tuples, dictionaries
• Maps, hash tables, graphs, trees, linked lists
• Search and Sort Operations
• Stacks and Queues

BIG DATA (A2)

• Big data Concepts & Hadoop
• Read/Write CSV, XML and JSON files
• Using Python with SQL Databases (MySQL or PostgreSQL)
• Using Python with NOSQL (MongoDB)
• Using Pandas datasets
• Big data and Pyspark
• Descriptive Statistics and Histograms with Python
• Data Visualisation with matplotlib, Seaborn and Dash

AI AND MACHINE LEARNING(A3)

• AI concepts & Types of machine learning
• Statistics: fundamentals, std deviation, percentile, data distribution, normal distribution, scatter plot, linear/polynomial and multiple regression, decision trees, testing of hypotheses, K-means clustering
• Data manipulation with lists, dictionaries and pandas. Data import, cleansing, data wrangling
• Build a neural network and make predictions. Pytorch for Deep Learning
• SciPy library and available functions
• Natural language processing using NLTP library – voice recognition, language translation, sentiment analysis
• General Adversarial networks
• Object detection and face recognition
• Train and test a machine learning model
• Design and implement a classifier in Python
• Visualisation tools

WEB DEV (A4)

• DJANGO concepts and the MVC framework
• Create HTML forms and submit in Python
• Apps, Files, Flow, Routes, Views, Create and use templates.
• Build models using MySQL
• Interact with APIs, JSON and XML
• Develop, test and host web pages

PYTHON PROJECTS

To help candidates master Python, they will normally to do at least ONE of the projects below:

BUSINESS: Develop a model for customer segmentation, loan/stock prices predictor.
SOCIAL MEDIA: Web scraping using Soup to collect social media posts, perform fake news detector and sentiment analysis of messages.
NETWORK SECURITY: collect network traffic, import/cleanse and build a classifier to predict network attacks similar to IDS/IPS
IOT: Rasberry PI for smart home solutions such as fire detection, measure soil moisture in the garden, face recognition to unlock door, etc
OTHERS: Build a chatbot for customer support, DL chatbot for personality predictor(HR systems), Bitcoin price prediction, credit card fraud detection, gender/age detection, etc

COURSE ORGANISATION & TIMING

We have created a schedule for this course to match with most availabilities.

The course is modular and candidates can take any combination from P1 and then A1- A4. Courses are hands-on(25% theory, 75% practice)

  • Monday - Friday (Between 10am - 5pm)
  • Course Materials and Online Content Provided
  • Duration is indicative and may include off-campus assignments and exams questions
  • Flexible Timetable
  • Special Packages + Payment Facilities

BENEFITS OF THIS COURSE

There are many benefits in becoming a Python Developer

Python is the second-highest paid computer language, according to Indeed. You can expect an average salary of USD 110,026 per year. Nothing to cry about! If you can land a job with Selby Jennings, you’ll earn the most. The average salary there is USD 245,862. Amazing!
One of the top benefits of Python is that it is easy to learn and fun to use. Its syntax, unlike most computer languages, reads like English, so it isn’t as stressful to learn as other programming languages. It was named after Monty Python’s Flying Circus, so you know someone had a sense of humor developing this code and thus made it simple to use.
Not only is Python easy to learn, but also, it’s flexible. Over 125,000 third-party Python libraries exist that enable you to use Python for machine learning, web processing, and even biology. Also, its data-focused libraries like pandas, NumPy, and matplotlib make it very capable of processing, manipulating, and visualizing data — which is why it’s favored in data analysis.
Thanks to the benefits of Python’s and its flexibility, you can find it in just about any industry. New Python programmers aren’t limited to just data science.

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INTERESTED IN THIS COURSE?

Infoclub Ltd has proudly served IT Professionals seeking to enhace their skillsets with the latest certification in IT with precision and excellence for over 30 years.

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Phone: +230 2411533

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