This course is designed for those who already have familiarity with the fundamentals of SQL and would like to understand the advanced concepts of SQL. Students will learn the art of breaking a big SQL statement into small pieces of queries and rebuilding it again. They will also have hands on various popular database platforms such as SSMS, Toad and Cloud to use Analytic SQL to aggregate, analyse and report, and model data using the SQL Analytic capabilities.
This course will let students learn about the Extract Transform and Load process, when it is used and why with the help of several advanced ETL tools such as SSIS, Informatica and Talend. At the end of this course, the student will be able to answer how to gather data from multiple sources in multiple formats, and move it to one or more data stores.
The two most powerful and demanding tools for data visualization are Tableau and PowerBI. This course will provide advanced skills to learn these tools. Students will practice hands on connecting the different data sources, joining tables and creating interactive reports or visualizations using the complex datasets.
Dashboards are the best means of communicating data to the audience. This course deals with the art of developing attractive and meaningful dashboards with the help of visualizations created. We will also teach how to publish the same dashboard into server for the audience to view the amazing work.
This course provides a broader introduction to machine learning and pattern recognition. The course will also make students aware of numerous use cases and applications, so that they will learn how to apply algorithms to build smart robots, text understanding, medical informatics, audio, database mining and other areas.
If you want to know how to improve the efficiency of your machine learning model and which data columns forms the best features, then this course will teach you all about it. After completing the course students will be able to answer when we need feature engineering and how to do it.
This course will teach you how to plan and write data models in Python, as well as build upon those models through an actual database. We will help students learn about the data modelling development process and then move ahead with the basic and advanced version. By the end of the course the student will be able to create highly valued and significant data models with Python.
This is step ahead of what is covered in the Wizkateers program of the data visualization course. Data Visualisation is such an important skill to have in order to become successful in the data science field. In this course we cover the remaining and more advanced platforms of analyzing data such as ggplot2 in R, Matplotlib in Python and Tableau to understand andbuild more interactive visualizations and make our students data visualization and storyteller experts.
Inside Kaggle you’ll find all the code and data you need to do your data science work. Use over 19,000 public datasets and 200,000 public notebooks to conquer any analysis in no time.
Students will have opportunity to participate in various competitions as a team with an assistant from a group of instructors and industry experts.