Brian Ngatia

I am an enthusiastic, motivated, and reliable backend software developer. I am skilled in programming using Python and Java and can comfortably use them in providing programming solutions. I am knowledgeable in HTML, CSS, and Javascript for web development.

I am also gaining additional knowledge in backend web programming using Django and Flask web frameworks. I have also worked on Machine Learning algorithms, especially in Natural Language Processing in Python. I am proficient in Web Scraping and Automation using Beautiful Soup and Selenium libraries in Python.

I am eager to learn new technologies and apply my existing knowledge to create systems that will make a change in society.

I have completed a three-month-long attachment period at Dedan Kimathi University in the Software Development department.

During my period there, I sharpened my software development and computing skills and gained experience in providing real-world IT-based solutions. I was responsible for assisting the development team in solving software issues and ensuring the smooth running of computing operations. I successfully created a department chat application that helped ease communication and file sharing among the department team members.

The system also allowed members to send notifications about upcoming events and share them as emails to the responsible members. The system significantly improved efficiency among the team as they avoided using social media applications such as Whatsapp to send messages as they may cause unnecessary distractions.

I am in my final year at Kisii University, pursuing a Bachelor's degree in Software Engineering. I will be graduating on 14th December 2022. My coursework has exposed me to various technologies including,

• Website Development using HTML, CSS, and Javascript.
• Java and Python programming
• Object-oriented programming
• Data Science and Machine Learning
• Database Systems (MYSQL)
• Software Design and Implementation
• Data Structures and Algorithms 

For my final year project, I created a political prediction system that leverages Machine learning technology to categorize data from social media platforms to compare the support that political candidates have. The system also detects hate speech in text and analyzes the comments fed to determine the levels of hate speech. The project was successful and achieved 97% accuracy in text categorization.