D213 - Advanced Data Analytics
Advanced Data Analytics prepares students for career-long growth in steadily advancing tools and techniques and provides emerging concepts in data analysis. This course hones the mental and theoretical flexibility that will be required of analysts in the coming decades while grounding their approach firmly in ethical and organizational-need-focused practice. Topics include machine learning, neural networks, randomness, and unconventional data sources.
Course Analysis
This course is structured around three main tasks, each designed to build practical skills in different aspects of data mining:
Task 1: Time Series Analysis Using ARIMA
In this task, I learned about the K-means clustering technique, a foundational tool for identifying groups within a dataset based on similarity. The hands-on application involved segmenting data into distinct clusters to uncover patterns. This technique was pivotal in understanding market segmentation and customer grouping, providing insights into data structuring for further analysis.
Task 2: NLP Using TensorFlow/Keras
The second task introduced me to Natural Language Processing (NLP) with an emphasis on utilizing TensorFlow and Keras libraries. This task was a deep dive into the world of machine learning models for text processing, where I explored how to preprocess textual data, create word embeddings, and build neural network models to understand language patterns. The practical application of TensorFlow/Keras provided a solid foundation in managing, modeling, and interpreting large sets of textual data. It was an enlightening experience to see how NLP techniques can be leveraged to analyze and make predictions based on human language data.
Final Thoughts
Advanced Data Analytics is a comprehensive course that equips students with the knowledge and skills to navigate the rapidly evolving field of data analysis. Through hands-on tasks with ARIMA and NLP using TensorFlow/Keras, I gained invaluable insights into time series forecasting and natural language processing. This course has significantly enhanced my analytical toolkit, preparing me for the challenges and opportunities in data-driven industries.
