CADS DATA SCIENCE TRAININGS & COURSES
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Get Ahead In Your Career with CADS Data Science Trainings & Courses
CADS Analytics & Data Science Trainings, Courses and Certifications with our expert, in-house team of Data Scientists. Whether you’re just starting out with Analytics using MS Excel, an experienced Data Scientist or working with Artificial Intelligence (AI), we have the training and certification you need.
A wide selection of in-person training classes
Specialized programs for graduates and professionals
Certifications available for you to be recognised for your skills
Engage in our online community of Analysts and Data Scientists
Explore CADS Analytics & Data Science Training Tracks & Courses
Modular Courses
Executive Business Education
Master Business Essentials To Make Better and Informed Business Decisions.
The Executive Business Education track is targeted at business executives and business users. The track provides a solid foundation in harnessing the power of Big Data and Analytics to help organizations seize strategic opportunities, gain deeper insights and deliver real business value.
The goal of the Executive Business Education track is to help participants acquire a firm grounding in Big Data and Analytics and an in-depth understanding of how it can be applied across different areas of the business.
Participants will also learn how to implement data focused initiatives that can address critical business challenges and add real business value.
In addition to Big Data and Analytics, this track also helps participants achieve fluency in the language of business by developing deep-seated problem solving skills and the confidence to contribute to business discussions and decision making.
Learning Outcome
Upon completion, participants should be able to demonstrate each of the following;
- Apply big data and analytics to reshape business model and operations
- Implement data-focused initiatives that create and capture more value
- Draw on Big Data to validate and influence organization’s long-term strategies
- Apply economic principles to business decision making and learn how to build and interpret financial statements
- Expand personal and professional network
Learning Path
Explore modules in this track;
1 to 3 days
4 days
8-9 days Learning Track
Enterprise Data Practitioner
Turn Data Into Effective Business Insights.
Enterprise Data Practitioner is a training program that super-charges Business Intelligence analysts with new skills to analyse and communicate insights effectively.
This track uses ubiquitous software that most organisations already have at their disposal such as Microsoft Excel and Tableau. It is designed to include a 2-day Data Storytelling session for analysts to become competent at conveying the outcome of their analytical work to key decision-makers in the organisation.
This course is best-suited for Business Intelligence Analysts looking to maximise the potential of their work.
Learning Outcome
Upon completion, participants should be able to demonstrate each of the following;
- Use PivotTables and Functions effectively to summarise and augment Data in Microsoft Excel
- Visualize Data & create dashboards for reporting with Microsoft Excel
- Assess Data distributions and statistical relationships with Microsoft Excel
Learning Path
Explore modules in this track;
4-7 hours (online)
1 day (optional)
3 days
2 days
1 day
2 days
17 – 18 days
Online Instructor-Led Learning
Associate Enterprise Data Analyst
Associate Enterprise Data Analysts Are Multilingual.
The Associate Enterprise Data Analyst (AEDA) track is a training program that provides analysts with the tools required for efficient data analysis on data retrieved from a variety of file types and/or relational databases in either Python or R. Participants walk away with the skills to explore data for patterns and insights. This course is best-suited for individuals looking to enter Data Analytics.
We know that programming can be a daunting task for newcomers and have included an ‘Introduction to Programming’ module that breaks down this barrier to entry. Participants can choose to learn modules in this course in either Python or R, which are both popular programming languages in the sphere of Data Analytics.
After learning the fundamentals, participants will learn how to clean dirty data and perform exploratory data analysis. Finally, participants are introduced to SQL (Structured Query Language) which is a language used to interact with relational databases and is common-place in most organisations today. Participants walk away with the skills to explore data for patterns and insights. This course is best-suited for individuals looking to enter Data Analytics.
Learning Mode
Online Instructor-led learning via webinar.
Learning Outcome
Upon completion, participants should be able to demonstrate each of the following;
- Understand the definition of a database and explain what a database management systems (DBMS) does
- Familiar with SQL Statements
- Ability to JOIN tables
Learning Path
Explore modules in this track;
4 hours (online)
3 days
6 days
2 days
2 days
1 day (optional)
2 days
Track Pre-requisit
11 – 16 days Learning Track
Enterprise Data Analyst
Investigate data to extract obvious or hidden information.
The objective of the course is to teach participants how to think in a data-analytics way, conduct or approximate experiments on business activity using R programming, analyze data rigorously and communicate results well, as well as summarizing achievements to present to decision-makers. The course is aimed at people with little to no experience in computer science, but with grounding of undergraduate-level mathematics.
Data Analytics (DA) is the process of investigating data to extract obvious or hidden information they contain. Commercial industries are increasingly utilizing data analytics technologies, techniques and tools to make information-aware or data driven business decisions.
The Enterprise Data Analyst track is a fast-paced practical introduction to the interdisciplinary field of data analytics, which is the study of how to use computer science, statistical methods and tests, coupled with a scientific mindset to extract knowledge from data.
This course is made out of nine Modules and requires participants to demonstrate the application of their learning through a Capstone Project.
Learning Outcome
Upon completion, participants should be able to demonstrate each of the following;
- Comprehend the principles, techniques, and practices relevant to Statistics
- Conduct Hypothesis Testing
Learning Path
Explore modules in this track;
2 days
2 days
1 day
Pre req: Inferential Statistics
2 days
2 days
2 days
Track Pre-Requisit
22 – 24 days Learning Track
Enterprise Data Scientist
A fast-paced practical introduction to the interdisciplinary field of Data Science
The Enterprise Data Scientist track is a fast-paced practical introduction to the interdisciplinary field of data science, which is the study of how to use computer science, statistics and a scientific mindset to extract knowledge from data.
The goal of the course is to teach participants to think in a data-scientific way, conduct or approximate experiments on business activity, analyze data rigorously and communicate results well. The course is aimed at people with no or little experience in computer science, but with a strong, undergraduate-level math background.
This course is made out of 4 core modules and requires participants to demonstrate the application of their learning through a Capstone Project.
Learning Outcome
Upon completion, participants should be able to demonstrate each of the following;
- Understand the landscape of machine learning possibilities
- Ability to train a model using simple supervised learning algorithms
- Ability to train and evaluate a model using training and/or test data
Learning Path
Explore modules in this track;
5 days
3 days
2 days
2 days
2 days
3 days
Track Pre-requisit
10 days Learning Track
Enterprise Data Engineer
Understand your data needs and create systems to store, compile, systematize, maintain and deploy your data for efficiency.
2 days
1 day
2 days
2 days
1 day
1 day
2 days
2 days
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