This course provides an overview of the fundamental concepts and practices in the fields of Data Science, Business Intelligence (BI), and Big Data. It explores the techniques, tools, and methodologies used to collect, analyze, and derive valuable insights from data, catering to the growing demand for data-driven decision-making in various industries.

The course focuses on teaching individuals how to use SQL Server product features and tools related to implementing a database server. This training provides students with the technical skills required to write SQL queries. This course on SQL Server is the basis for all various roles related to Data Science like business intelligence, Data Scientist, Big Data Developer, Database Administration.

This course is designed to equip participants with the essential skills and knowledge needed to effectively utilize Microsoft Power BI for data analysis and visualization, combined with a strong foundation in statistical concepts and techniques. It provides a comprehensive understanding of both statistical methodologies and the practical application of Power BI for making data-driven decisions. After completing this course, students will be able to create reports, KPIs and dashboards using Power BI, the latest reporting technologies, and methods.

The Python Programming Course is designed to take participants from beginners to proficient Python developers. Whether you're new to programming or seeking to expand your coding skills, this course provides a comprehensive exploration of Python's versatility and applications. Through a blend of theoretical lessons, hands-on exercises, and real-world projects, participants will gain a solid foundation in Python programming and develop the ability to create a wide range of applications.

The course provides an in-depth and hands-on introduction to the topic of machine learning. The fundamental ideas, methods, and algorithms of machine learning are covered in this course. The course includes a thorough study of statistics, a variety of machine learning techniques related to both supervised, unsupervised machine learning, topics  related to Deep Learning and an introduction to neural networks.

Advanced skills in Python is crucial for many data science roles. In this course, you will continue to build on the Python programming skills you acquired in the previous class by implementing machine learning using python libraries like Tensorflow, Pytorch, Scikit-learn You will learn all the advanced Python libraries that are being used in the real world by data scientists.  Data Science with Python training help you advance your career as a data scientist. 

This course is designed to teach students how to integrate themselves into the Canadian job market. In 4 short classes, we look at the kind of mindset that is needed to be successful in the job search process, how to shape the CV and cover letters, we practice interview skills, and much more. 

In the last stage of your data science training, the newly acquired skills will be put into practice through a real-world project. The student will learn how to tackle a practical, industry-relevant problem by focusing on mentorship sessions for data processing and model creation. The project will provide you an opportunity to practice it in a practical setting.