Data Science Classes Sydney

Learn to problem solve, and effectively communicate, like an analyst. This course teaches you to use industry-standard tools to make ethical, data-driven decisions. Experience hands-on training to master SQL, Excel, Tableau, PowerBI, and Python – tools listed in virtually every data analytics job posting across industries.

In this comprehensive data science program, individuals will learn a variety of critical skills to become a data scientist. Students will learn to code with Python, create machine learning models, automate tasks like web scraping, and interact with databases using SQL. Topics include data analysis with Python's Numpy and Pandas packages, data visualization, predictive analytics, machine learning, SQL querying, Python automation, and web scraping. Students will learn hands-on by working in Python and SQL and will complete the program with the skills they need to enter the field of data science. This program offers flexible scheduling and provides a free retake for students to refresh the material.

Create robust predictive models with statistics and Python programming. Build confidence and credibility to tackle complex machine learning problems on the job. This course is offered in person and live online, in a remote classroom setting.

This online data science program is meant to get students ready for a career in data science. The program covers the key components for data science, including SQL, Python, statistics, and machine learning. Students will start coding in Python using Jupyter notebooks, learn the statistics behind machine learning, apply machine learning techniques, and work on data science projects in this data science course. Students will also receive career coaching and job support during the program for help finding a job in data science. The online program offers flexible scheduling options, including full-time over 5 months, part-time over 10 months, and self-paced for up to 15 months.

In this course, students expand their Python programming skills into machine learning and algorithms that can independently learn patterns and make decisions. The course begins with linear and logistic regressions, the most time-tested and reliable tools for approaching a machine learning problem. Students then progress to algorithms with a different theoretical basis, such as k-nearest neighbors, decision trees, and random forest. This will bring important statistical concepts to the forefront, such as bias, variance, and overfitting. Participants also learn how to measure the accuracy of your models, as well as tips for choosing effective features and algorithms.

In this data science bootcamp, students will build programming skills and data analysis skills using Python. This course is open to beginners and is meant to get individuals up and running with Python programming and data science to generate insights from data. Topics covered include programming fundamentals, working with data frames, data analysis, data visualization, and statistical analysis. This course offers flexible scheduling options and a free retake for students to refresh the materials.

Data Science Flex is a 6-month part-time program that will prepare you to to be a data scientist. This program comes with a tuition back guarantee if you can't land a job within 6 months after your graduation. To be accepted into this program, you will have to complete 3 weeks of prepwork and pass an assessment test before you start. Once you're accepted, you'll learn how to clean data using Python, query data using SQL, learn how to train and evaluate supervised and unsupervised machine learning models, and choose a track to specialize. You can deepdive in natural language processing, big data and spark, and deep learning with TensorFlow and Keras.

This data science program is a beginner-friendly bootcamp designed for individuals interested in learning the best practice of working with data and understanding how to gain insights from large data sets. In this hands-on bootcamp, students will get an overview of data science, including the various roles within data science and how to recognize and solve problems with data science. Students will also discuss how to use some well-known statistical models and how models fit into a data science project. Finally, students will explore various tools, including data visualization, analytical, and modeling tools essential in the field of data science.

This Python and machine learning course is a 2-day bootcamp designed for individuals with some familiarity with Python programming looking to advance their skill set. In this hands-on bootcamp, students will learn how to use some Python data science libraries and various machine learning techniques. Day one of the bootcamp focuses on introducing students to two data science libraries (NumPy and Pandas), best practices for preparing data, an intro to machine learning, and regression analysis. Day two starts off with cross validation and regularization of data, concludes with classification, and brings everything learned in days one and two together.

This SQL bootcamp is a beginner-friendly workshop designed for individuals with no prior knowledge of SQL who are eager to learn. In this hands-on workshop, students will learn the basics of SQL syntax and how databases are organized. Students in this course will also learn how to query data, aggregate data with statistical functions (SUM, AVG, COUNT, etc.), group data, and use conditional operators (=, <, >, etc.) to sort and filter data, and much more. Students will also learn when and how to use UNIONs and JOINs to merge data to spot trends and other insights.

Harness Excel, SQL, and Tableau to drive powerful analysis and insights. Build confidence and credibility to apply this versatile skill set to countless jobs. This course is offered in person and live online, in a remote classroom setting.

This advanced SQL course is a 3-hour workshop designed for individuals already familiar with SQL who are looking to take their skills to the next level. In this advanced hands-on workshop, students will dive into advanced calculations and techniques to work with data more effectively through SQL. Students in this course will also learn concepts like Text Searching, Views, and Stored Functions and Procedures. Students will also be provided with resources to hone their skills and practice the concepts covered in the course.

In this comprehensive Python course, participants will learn how to use Python for data analysis and data science projects. This beginner course starts with the basics of Python programming and foundational coding concepts. Students then learn how to leverage key data packages like Pandas, Numpy, Matplotlib, and Scikit-learn to start analyzing and visualizing data with Python. Students will receive a customized ebook for their ongoing reference.

In this introductory, 2-day SQL course, participants will learn the basics of databases and start querying databases with SQL. Participants will get comfortable with databases and start performing basic querying techniques like SELECT, ORDER, SUM, and GROUP BY. This course is intended to give students a fundamental understanding of the use of SQL for database management.

This 2-day advanced SQL course is designed for individuals who want to better understand database structure and querying data. Specifically, the course will cover connecting to a SQL server, executing a query, adding a condition to a query, using functions to make calculations, organizing data, and retrieving data from multiple tables. Students will be able to apply what they learn to PostgreSQL, MySQL & MariaDB and Oracle among others.

This 12-hour machine learning with Python course provides students with the foundational theory and skills needed to design machine learning algorithms to help make sense of data. The course covers a range of introductory machine learning and Python concepts, including an introduction to Python and machine learning, some background as to why Python is great for machine learning, getting started with Python, basics of data structures, syntax for conditional statements, working with functions, using PANDAS, data visualizations, linear regression, general statistics concepts, model evaluation metrics, decision trees, and more.

This data analytics course is a 1-day bootcamp designed for individuals interested in learning the best practice of working with data and understanding the data analytics roadmap. In this hands-on bootcamp, students will learn how data can help inform decision making, understand the data analytics workflow, and gain exposure to some of the most common tools used for data analysis. Students will also learn how to ask the right questions that can be answered with data, clean and analyze data with standard spreadsheet software (Excel/Google Sheets), and use Tableau to create dynamic visuals.

In this course, participants will learn the fundamentals of relational databases and begin writing SQL queries to extract data from databases. They will receive essential training in the basics of the three core components of SQL: relational DBMS, SQL, and Microsoft SQL Server. Students will receive a customized eBook for their ongoing reference.

In this course, participants with a basic knowledge of SQL learn the next level of querying, including subqueries, logic statements, joins, and more. They will master views and data conversions and develop their skills by writing advanced functions to gain more control in their relational DBMS (Database Management System). Students will learn the tools and techniques related to the following commands: Create Views, Subqueries, and Math Functions & Logic Statements. Students will receive a customized eBook for their ongoing reference.

In this course, participants at an intermediate skill level with SQL will master advanced processes and gain the skills necessary for database management. They will learn advanced processes and controls, create stored procedures, connect to external data sources such as Microsoft applications, and manipulate data with constraints. This expert-level course will focus on the following core tasks: creating a database, importing data from external sources, and building database infrastructure and constraints. Students will receive a customized eBook for their ongoing reference.