Dse Africa Ultimate Python Meetup Recap

Recently Data Science East Africa in collaboration with Lux Tech Academy and Moringa School organized the Ultimate Python Meetup and it was all blissful. It couldn’t get any better than having great speakers rolling on with various topics including;

• Fundamentals of Python
• Data Structures and Algorithms
• Application / Career paths of Python
• Myths and Misconceptions about data Science

Let’s discuss these areas covered one by one;

Fundamentals of Python

Python is an interpreted, object-oriented, high-level, and general-purpose programming language. Its built-in data structures and availability of standard libraries that are usable free of charge make it attractive and popular for Rapid Application Development. It is a language that can show people a range of things that can be done with programming i.e.; Web development, web scraping, desktop applications, data science, and machine learning. Because of its multiple purposes, learning python can enable one to go from zero to hero regarding programming fundamentals.

Amongst the fundamentals of python are understanding variables, arithmetic use, conditional executions, iterations, functions, lists, dictionaries, tuples, classes & objects, and handling exceptions. These form part of the backbone part of understanding the python programming language.

Data Structures and Algorithms

In the intro to data structures and algorithms, we shared that data structure is some way of rendering the data elements in terms of some relationship for better storage and organization. An algorithm on the other hand refers to a core logic solution or procedure for doing some predefined tasks. Basic data structures include;

• Arrays
• Linked list
• Stack
• Queues
• Graphs
• Trees
• Hash tables

Algorithms depend on their time and space complexities and the best of these criteria is chosen. Some basic algorithms include;

• Greedy algorithms
• Divide & Conquer algorithms
• Dynamic programming algorithms Problem-solving in real life is done with the help of data structures and algorithms.

Application / Career paths of Python

Python programming language is quite versatile hence one can choose an area of specialization from a variety of fields that include;

• Data Science / Data Analytics – python gives room for analyzing data through its libraries i.e., Pandas, SciPy
• Machine Learning – building computer-based systems that acquire some knowledge enabling them to make valuable predictions.
• Automation purposes – the simplicity in python enables one to automate even simple tasks like email manager hence the increase in task complexity leads to adverse automation.
• Desktop applications – python enables you to create GUI applications that work across platforms
• Web applications – backend creation of web pages is made through frameworks like Django, Flask, etc.
• DevOps – deployment, and automation of software can be done through python. These are just among the few mentions of the application of python.

Myths and Misconceptions of Data Science

At the current age, most people in the limelight of tech are talking about Data Science. Some say it's just and that it would fade away with time but the clear point is that managing data is becoming some of the success determinants in organizations. Data Science is giving means of analyzing and managing this data for better use. There are possibilities for data science automation but data scientists are needed to perform advanced operations in manipulating these machines. Machines can't fully run themselves hence data science won't be replaced by AI. Apart from learning the tools needed for data science i.e., coding, maths, and statistics, one should have proper problem-solving skills and determine when to apply the tools and algorithms. Lastly, data science is not building models all day long. It includes data acquisition, data cleaning, data preparation, visualization, and much more.

In conclusion, Python is a highly recommended language for use.