BE A CERTIFIED DATA SCIENTIST (FOR ENTERPRISE)

MORE THAN 33 RUNS & OVER 500 PROFESSIONALS TRAINED

As data continues to drive strategic decision-making in every sector, the demand for skilled data scientists is at an all-time high. The CDS program is relevant for professionals who aspire to transition into data science roles or enhance their current analytical capabilities. It is particularly pertinent to sectors where data can provide a competitive edge, such as technology, finance, healthcare, and government operations, including military.

The Certified Data Scientist (CDS) program is a comprehensive training suite designed to develop essential data science skills using Python, from foundational knowledge to advanced machine learning and project execution. This program is broken down into three distinct parts, each with two specialized workshops that guide participants through the journey of becoming skilled data science practitioners. By the end of the program, participants will have a thorough understanding of data analysis techniques, machine learning algorithms, and the execution of end-to-end data science projects.

UNIQUELY DESIGNED BY RESEARCH ROOM (rR) and delivered through JCube
Our certification model is uniquely designed by founders of Research Room (rR)*, an AI consulting and implementation group that was co-founded by a team of Singaporean Ph.Ds who have worked on bespoke implementations of data driven strategies that delivers complex prediction and decision-making capabilities to thousands of clients and organizations. The programme is well-supported by a network of experienced Data Scientists and Analysts. Course is short and compact, targeted to get you industry ready and certified within the shortest time, working around your busy schedule.

Certified Data Scientist Programme Objectives:

• 1. Provide an in-depth understanding of Python programming and its application in data science.
• 2. Equip participants with robust skills in exploratory data analysis and data visualization techniques.
• 3. Develop proficiency in building and evaluating both supervised and unsupervised machine learning models.
• 4. Offer practical experience in project scoping, requirements analysis, and execution within a data science framework.
• 5. Cultivate the ability to communicate findings and insights effectively from data science projects.

This workshop is dedicated to introducing the Python programming language and its application in data science. This workshop provides an essential foundation in Python coding, focusing on the language’s capabilities for data manipulation and analysis. Emphasizing practical skills, it offers participants a thorough grounding in Python’s core concepts, preparing them for more advanced data analysis tasks in subsequent modules.

This workshop builds upon the Python programming skills acquired in Workshop 1, guiding participants through exploratory data analysis (EDA) techniques and data visualization using Pandas, Matplotlib, Seaborn, and Plotly. This workshop emphasizes the importance of EDA in uncovering patterns, detecting anomalies, and testing hypotheses with visual methods. Additionally, an introduction to creating web applications with Streamlit for data science will be provided, enabling participants to share their insights interactively.

This workshop delves into the core concepts and techniques of supervised machine learning, which is pivotal for predictive analytics in various domains, including the military. The workshop covers the full spectrum of supervised learning, from understanding the fundamental principles to applying and evaluating models such as logistic regression, decision trees, and ensemble methods. Participants will engage in hands-on exercises to solidify their understanding, culminating in the development of a trained model on a relevant dataset.

In Workshop 4, participants will explore unsupervised machine learning techniques that are essential for discovering hidden patterns and relationships in data without pre-labeled responses. This workshop will provide a solid foundation in unsupervised learning concepts, clustering techniques, dimensionality reduction, and association rule learning. Participants will gain hands-on experience applying these methods to datasets, resulting in a comprehensive understanding of how unsupervised learning can be leveraged for insightful data analysis.

This workshop tailors data science project scoping and requirements analysis within the military context, emphasizing the initial stages critical for successful project execution. It introduces participants to the processes of defining project objectives aligned with military operational goals and effectively communicating with stakeholders. The workshop extends to cover the essentials of data science deployment, focusing on the use of version control with Git and continuous integration/continuous deployment (CI/CD) workflows.

This workshop serves as the capstone event for the Certified Data Scientist program, consolidating the knowledge and skills participants have acquired through a guided project. This workshop allows participants to apply their data science skills within a military context, using real or simulated data to solve practical problems. Emphasizing the end-to-end process of a data science project, this workshop encompasses dataset preparation, model application, performance evaluation, and the communication of findings through a final presentation.

Individual Rate:
S$1600 per pax for a 2 day workshop

Corporate Rate:
Less than 8 pax ($5,500 for a 1 day workshop and $11,000 for a 2 day workshop)
8 – 15 pax ($6,000 for a 1 day workshop and $12,000 for 2 day workshop)

Note: Our course fees are exempt from GST charges.

1. Cancellation by Client

1.1. Notification:

All cancellations must be submitted in writing via email to admissions@jcube-institute.com.

1.2. Refunds:

– Up to 30 days before the class start date: Full refund minus a processing fee of SGD 800 per class.
– 30 days or less before the class start date: No refund.

1.3. Substitutions:

The client may substitute participants up to 5 days before the class start date without any additional fees.

2. Cancellation by JCube Institute

2.1. JCube Institute reserves the right to cancel the class. In such cases, clients will be notified at least 10 days before the class start date.

2.2. Refunds: In the event of cancellation by JCube Institute, clients will receive a full refund of the class fees.

3. Force Majeure

In the event of circumstances beyond our control (e.g., natural disasters, pandemics, government restrictions), JCube Institute reserves the right to reschedule or cancel the class. Clients will be offered the option to attend on the new date or receive a full refund.

4. Rescheduling

4.1. Client-Initiated Rescheduling: Requests to transfer reschedule the class date must be made at least 14 days before the original class start date. Transfers are subject to availability and a rescheduling fee of SGD 500 per class may be levied.

4.2. JCube Institute-Initiated Rescheduling: If JCube Institute reschedules the class, clients will be offered the option to transfer to the new date or receive a full refund.

5. Attendance Requirements

5.1. Participation: Participants are expected to attend up to 75% of scheduled sessions of the training class to receive any certificates of completion associated with the course.

5.2. Punctuality: Participants should arrive on time for each session. Late arrivals may be allowed at the discretion of the instructor but may result in missing critical content.

5.3. Absenteeism:

– Notification of Absence: If a participant is unable to attend a session, the client must inform JCube Institute as soon as possible. Do note that participants are expected to attend up to 75% of scheduled sessions of the training class to receive any certificates of completion.

LEARN FROM VETERAN DATA SCIENTISTS AND A.I. EXPERTS

JCube faculty have collectively trained more than 10,000 professionals are among the most respected and passionate practitioners and leaders in the field of digital science and transformation. Their expertise provides the highest quality of instruction to learners. Faculty also teach Data Science at renowned Universities at Undergraduate, Masters and Doctoral Levels and are known to be the best teachers who are patient and experienced in simplifying difficult concepts for learners to grasp easily.