Ndiene Tshivhase
Graduate Information Technology
Sibasa,Limpopo
Summary
Graduate in IT with a diploma, specialized in software development and business analysis. Proficient in Java and Python, with expertise in data science and experience working with Windows OS. Detail-oriented, innovative, and passionate IT professional, ready to contribute to any organization's success.
Overview
1
1
year of professional experience
6
6
years of post-secondary education
5
5
Certifications
Work History
Data Science Master's Program
Deviare
Johannesburg
06.2022 - Current
- Utilized analytical and technical expertise to provide insights and proposals to support business improvement.
- Build predictive models using various machine-learning tools to predict diabetes in patients.
- Develop algorithms using Natural Language preprocessing and Deep Learning for a better chatbot user experience.
- Demonstrate knowledge and execution of application programming interface development
Education
Diploma - Information Technology
Vaal University of Technology
Vanderbijilpark 02.2018 - 11.2021
National Senior Certificate -
Lucas Ratshalingwa Secondary School
Limpopo, Thohoyandou 01.2012 - 11.2017
Skills
Teamwork and Collaboration
MS Office
Interpersonal Communication
Machine learning
Java NetBeans HTML Python
Attention to Details
Certification
HTML, CSS, and Javascript for Web-Developers [Coursera]
Project Work
- Cat vs Dog Classification Using CNN, the main goal for this project was to develop a system that can identify images of cats and dogs, the input data was analyzed and the output was predicted, the model was able to differentiate images of cats and dogs.
- Comcast consumer complaints, the task of this project was to perform an analysis from the given data and provide a trend chart for the number of complaints at monthly/ daily granularity levels and present further insights. I completed this project using various tools such as pandas, NumPy, matplotlib, and seaborn.
- Building a chatbot from scratch in python (Using NLTK) the chatbot was built using deep learning techniques, it was trained on the dataset which contained categories(patterns and responses), a special recurrent neural network to classify which category the user’s message belongs to and then it provides a random response from the list of responses.
Work Availability
monday
tuesday
wednesday
thursday
friday
saturday
sunday
morning
afternoon
evening
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Quote
How many ideas have there been in the history of the human race that were unthinkable ten years before they appeared?
Fyodor Dostoevsky
Timeline
Tableau Training-[SimpliLearn]
11-2022
Deep Learning with Keras and TensorFlow-[SimpliLearn]
10-2022
Data Science with Python-[SimpliLearn]
07-2022
Data Science Master's Program
Deviare
06.2022 - Current
HTML, CSS, and Javascript for Web-Developers [Coursera]
12-2021
Crash Course on Python-[Coursera]
10-2021
Diploma - Information Technology
Vaal University of Technology
02.2018 - 11.2021
National Senior Certificate -
Lucas Ratshalingwa Secondary School
01.2012 - 11.2017