Big Data Analytics and Cloud Computing

Big data analytics helps organizations harness their data and use it to identify new opportunities. That, in turn, leads to smarter business moves, more efficient operations, higher profits and happier customers. Becoming a data scientist takes more than the understanding of basic skills like statistics and programming in various languages. The need to develop one area of technical
analytic expertise while being conversant in many others is very crucial. Going beyond descriptive analytics has become essential to meet the complexities of information requirement for decision making as well as developing strategies to drive greater profitability, improved performance and competitiveness. On the other hand, companies are increasingly storing large amounts of data online due to the increase in Big Data. Cloud computing is becoming increasingly vital for not just the software developers but also in the field of big data analytics: cloud computing makes expanding computing power and deploying data solutions much easier and is therefore handy for data scientists who are digging into large datasets.

This course builds expertise in advanced analytics, data mining, predictive modelling, as well as cloud computing and Microsoft Azure. It provides a comprehensive introduction to data science, covering key Python programming concepts, data manipulation with Numpy and Pandas, and data cleaning techniques.

The aim of the course is to introduce the trainees to the important big data management techniques, analytical tools and cloud computing (MS Azure).

Participants will learn how to work with datasets, including loading, storing, and preparing data, as well as performing data wrangling tasks like joining and reshaping.

The course also covers big data management with Apache Hadoop and MongoDB, as well as exploratory data analysis and visualization.

Participants will explore machine learning techniques, including regression models and supervised/unsupervised learning, and gain experience with SQL for database management in Python. Advanced topics such as text mining, sentiment analysis, and big data frameworks are also addressed, along with cloud computing concepts using Microsoft Azure.

By the end of the course, participants will have the skills to apply data science methods and work with large-scale data systems