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This Data Scientist course, delivered by Simplilearn in collaboration with Microsoft Azure, accelerates your career with real-world training in data science. Offering extensive training on in-demand skills like Python, SQL, machine learning, deep learning and generative AI, you'll gain hands-on exposure to key tools and technologies. The program includes live virtual classes, practical projects, and an integrated blended learning approach, ensuring you're job-ready as a data scientist.
In this Data Scientist course, you will:
Your qualification is the start. This program helps you turn study into real work, real contacts and real outcomes.
Turn your qualification into real Australian work experience. Complete 80% of your course and apply for a 12-week internship with a top host company, delivered with Career Success Australia. Past placements include NAB, BHP, PwC, Telstra and IBM.
Get in touch to know more.*
*Terms and conditions apply.
Our online Data Scientist course is a highly comprehensive and extensive course that upon completion, showcases your rich understanding and industry-related training in the data science field. The applied knowledge and hands-on skills you will gain come from working on various simulations, real world projects, and case studies throughout this course. The course content is summarised below.
Master Python programming from the ground up with this beginner-friendly refresher. Work through data types, operators, loops and conditional logic, then move on to error handling and functions. Gain hands-on experience with Python, the go-to language for data science, and learn to apply AI assistance to strengthen your analytics workflows.
Course delivery format: online learning + live virtual classes
The SQL Certification Course is ideal for those aiming to become SQL developers or data analysts and is perfect for improving database management expertise. This beginner-friendly course includes fundamental to advanced SQL topics. Participants will master data storage, retrieval, and manipulation using SQL.
- Lesson 01: Course Introduction
- Lesson 02: Introduction to SQL
- Lesson 03: Database Normalization and Entity Relationship (ER) Model
- Lesson 04: MySQL - Installation and Setup
- Lesson 05: Working with Database and Tables
- Lesson 06: Working with Operators, Constraints, and Data Types
- Lesson 07: Functions in SQL
- Lesson 08: Subqueries, Operators, and Derived Tables in SQL
- Lesson 09: Windows Functions in SQL
- Lesson 10: Working with Views
- Lesson 11: Stored Procedures and Triggers in SQL
- Lesson 12: Performance Optimization and Best Practices in SQL
Course delivery format: online learning + live virtual classes
Build the statistical foundation that underpins all of data science. Define statistics and the essential terms related to it, explain measures of central tendency and dispersion, and comprehend skewness, correlation, regression and distribution. By the end of this course, you will be able to make data-driven predictions through statistical inference.
- Lesson 01: Course Introduction
- Lesson 02: Introduction to Statistics
- Lesson 03: Understanding the Data
- Lesson 04: Descriptive Statistics
- Lesson 05: Data Visualisation
- Lesson 06: Probability
- Lesson 07: Probability Distributions
- Lesson 08: Sampling and Sampling Techniques
- Lesson 09: Inferential Statistics
- Lesson 10: Application of Inferential Statistics
- Lesson 11: Relation between Variables
- Lesson 12: Application of Statistics in Business
- Lesson 13: Assisted Practice
Course delivery format: online learning
Gain proficiency in Python tools and techniques essential for data analytics. Develop crucial skills needed for various data science roles through a comprehensive learning approach. Engage in blended learning to understand data analytics concepts thoroughly. Explore practical applications for hands-on experience. Advance your data science career with specialised training.
- Lesson 01: Course Introduction
- Lesson 02: Introduction to Data Science
- Lesson 03: Essentials of Python Programming
- Lesson 04: NumPy
- Lesson 05: Linear Algebra
- Lesson 06: Statistics Fundamentals
- Lesson 07: Probability Distribution
- Lesson 08: Advanced Statistics
- Lesson 09: Pandas
- Lesson 10: Data Analysis
- Lesson 11: Data Wrangling
- Lesson 12: Data Visualization
- Lesson 13: End-to-End Statistics Application with Python
- Free Course: Advanced Statistics
Course delivery format: online learning + live virtual classes
Achieve career success with our extensive Machine Learning course, featuring over 40 hours of applied learning and interactive labs. Solidify your understanding with four hands-on projects and benefit from mentoring support throughout your learning journey. Master essential machine learning concepts for certification and acquire the skills necessary to become a successful machine learning engineer.
- Lesson 01: Course Introduction
- Lesson 02: Introduction to Machine Learning
- Lesson 03: Supervised Learning
- Lesson 04: Regression and Applications
- Lesson 05: Classification and Applications
- Lesson 06: Unsupervised Algorithms
- Lesson 07: Ensemble Learning
- Lesson 08: Recommender System
- Free Course: Advanced Statistics
Course delivery format: online learning + live virtual classes
Learn to deploy deep learning tools using leading AI/ML frameworks while exploring core concepts and real-world applications. Understand how deep learning differs from machine learning and work with neural networks, backpropagation, TensorFlow 2 and Keras. Build models in PyTorch, study CNNs, RNNs, autoencoders and transfer learning, and master performance tuning and interpretability.
- Lesson 01: Course Introduction
- Lesson 02: Introduction to Deep Learning
- Lesson 03: Perceptron
- Lesson 04: Deep Neural Networks (DNN)
- Lesson 05: TensorFlow 2
- Lesson 06: Model Optimisation and Performance Improvement
- Lesson 07: Convolutional Neural Networks (CNN)
- Lesson 08: Transfer Learning
- Lesson 09: Object Detection
- Lesson 10: Recurrent Neural Networks (RNN)
- Lesson 11: Transformer Models for NLP
- Lesson 12: Getting Started with Autoencoders
- Lesson 13: PyTorch
Course delivery format: online learning
Data Science Capstone project provides an opportunity to apply the skills learned throughout the Data Science course. Through dedicated mentoring sessions, you'll tackle a real-world, industry-aligned Data Science problem, covering everything from data processing and model building to fine-tuning and presenting your business results and insights in a dashboard. This project serves as the final step in your Data Science training, enabling you to demonstrate your expertise to potential employers.
Course delivery format: online learning + live virtual classes
Optional electives are available as part of this Data Scientist course.
These are not mandatory to complete, but are available as additional courses to study if you are interested in expanding your knowledge and further implementing your skills.
This Data Scientist online certification training includes industry-relevant projects from various industries to help you master concepts of Data Science.
Some of the various projects you will be working on are highlighted below:
Digital certificates are the new way for Upskilled and Simplilearn graduates to demonstrate their hard-earned knowledge and skill sets.
You will receive individual certificates after each short course. Additionally, upon completing the entire bootcamp, you will earn a certificate that demonstrates your competence and expertise as a data scientist. You will also receive Microsoft course completion certificates through the Microsoft Learn portal for the Microsoft-aligned courses in this program.
Set yourself apart from the competition with the Data Scientist course certificate. This is your ticket to get your foot through the door and proof that you have applied data science knowledge and skills to real-world projects, simulations and case studies, making you job ready.
You worked for it, you earned it! Share your achievement loud and proud! Talk about your Data Scientist online course certification on LinkedIn, Twitter, Facebook. Add it to your CV to stand out and showcase to your employers.
To select the right course, identify your career goals and current skill level—whether you're a beginner looking to understand basic concepts or an experienced professional seeking advanced machine learning techniques. Consider the course's focus areas, such as data analysis, machine learning, or specific tools like Python or SQL, to ensure it aligns with your desired career path.
Yes, data science skills like statistical analysis, data visualisation, and programming are highly transferable across various sectors, including finance, healthcare, marketing, and logistics. These skills help in decision-making, predictive modelling, and process optimisation, making them valuable in almost any industry that relies on data-driven insights.
You'll need access to Python and tools such as SQL for database management, Jupyter Notebook for coding and experimentation, and data visualisation software like Power BI. Some courses might also require cloud-based platforms like Microsoft Azure or AWS for machine learning projects.
Start by familiarising yourself with basic programming skills, particularly in Python, as it is the language used throughout this course. Review foundational statistics concepts, such as probability, regression, and hypothesis testing, and explore basic data visualisation techniques.
Key soft skills include critical thinking for interpreting complex data patterns, problem-solving for developing data-driven solutions, and effective communication for presenting insights clearly to stakeholders. Adaptability is also crucial, as the field is constantly evolving with new tools and methodologies.
You’ll have access to live sessions, Q&A forums, and one-on-one consultations for personalised guidance. Instructors provide feedback on assignments and projects, helping you understand complex topics and apply concepts to real-world scenarios.
Once enrolled, course materials are typically available on an online learning portal, where you’ll have access to lectures, readings, datasets, coding notebooks, and assignments. The portal allows for instant access, making it easy to manage your learning resources throughout the course.
An Online Bootcamp is an intensive and accelerated learning program made up of a collection of self-paced eLearning components and live online classes that students are required to attend.
The Online Bootcamp program curriculum contain a combination of specifically chosen courses and career-critical skills that are aligned to a job role.
A Short Course on the other hand are shorter courses that is designed to target developing a specific skillset or topic. They generally are much quicker to complete than Bootcamp Programs.
Professionals with Data Science expertise are constantly growing in demand and has very good career opportunities for advancement and growth. Careers in the data science field have lucrative salaries.
With a consistent learning schedule and constant study hours, you can get through the course in about 5-7 months.
To enrol in this Data Science course, you will need a foundational understanding of data analytics, basic knowledge of statistics, and a basic understanding of any programming language. No related degree is required; this course is open to learners from diverse backgrounds.
Data science students come from a diverse range of backgrounds. From seasoned professionals to non-data or non-technical background, the Data Scientist bootcamp is open to everyone of any background, whether they hold a related degree or not.
Examples of students who study the Data Science Bootcamp have transitioned into data science from the following backgrounds:
Data Scientists are high in demand and are ranked among the top fields in Linkedin's Job Reports for the last three years and running. According to the latest information, data scientist roles are growing annually at 37%.
As such, Data Science Bootcamps are increasingly valued due to their emphasis on a hands-on focused and immersive approach. These days many organisations value skills that are job ready and demonstratable, and Bootcamps are an appraised path to achieve this practical experience.
Yes, upon completing the course program and projects, you will gain a Data Scientist certification as a demonstration of your applied practical skills and knowledge, which you can showcase in your CV.
To enrol in this Data Scientist Bootcamp, you'll need to first submit an enquiry form via our website. You'll need to provide the following details:
Once you've submitted your online form, one of our education consultants will be in touch within 48 hours.
During the consultation, you'll be able to ask questions regarding payment options, learning content and what career outcomes you can pursue if you complete your studies.
Retain your existing answer, and consider adding AI/ML Engineer and MLOps Engineer to the list of roles — the addition of Deep Neural Networks and the MLOps electives now genuinely supports those outcomes, and they are high-volume search terms.
There are various ways to become a Data Scientist. One of the renowned ways to enter the field of data as a data analyst is through immersive learning such as bootcamps.
The Data Scientist Bootcamp co-developed with IBM provides you with an in-depth understanding into world of Data Science, concepts, tools and methodologies.
Designed with a unique interactive environment, the Data Science Bootcamp will set you up for success as a data scientist and excel in your career. You will sharpen your ability to master high level technologies such as R, Python, Machine Learning techniques, data reprocessing, regression, clustering, data analytics with SAS, data visualization with Tableau, and an overview of the Hadoop ecosystem. Upon completion you will earn an industry-recognized certificate partnered with IBM that will strongly portray your new skills and on-the-job expertise as a Data Scientist.