Master Data Science. Get Certified. Stay Ahead.
Future-Proof Your Career with Data Science Certification
Validate your expertise with the Certified Data Science Specialist (CDSS) credential.
Gain hands-on experience, industry recognition, and career-boosting skills.
Why Data Science Certification Matters?
In 2025, obtaining a data science certification is increasingly vital for professionals aiming to enhance their careers in this rapidly expanding field.
Data science industry
is booming, projected to reach
by 2025.
(di47studio.com, 2024)
Candidates possessing
certifications are
more likely to
secure employment.
(digitaldefynd.com, 2025)
Certified data science
earn up to
more than their
non-certified counterparts.
(digitaldefynd.com, 2025)
It’s Time to Earn Your Credibility with Our
Certification Program!
The Certified Data Science Specialist (CDSS) program offers a comprehensive curriculum, covering fundamental data science concepts to equip participants with the skills necessary for success in this dynamic field.
Tailored for professionals, academics, and aspiring data scientists, the program focuses on building expertise in data analysis, machine learning, and data-driven decision-making.
Learn At Your Own Pace,
Select The Right
Level for You!
Basic Level
Advance Level
Why You Should
Join This Program
Build a Professional Portfolio with Real-world Projects
Work on Mini Projects that Reflect Real Industry Challenges
Master Practical Data Science Skills to Meet Industry Demands
Globally Recognized Certification in
26 Countries
Across Asia
Certificate Valid for a Lifetime
Intensive Class
Test Preparation with Expert
Get Bonus
Cheat Sheet Code
PROGRAM SYLLABUS
What You Will Learn in
This Program
This Certified Data Science Specialist (CDSS) will help you develop key data science skills through hands-on learning and real-world case studies. You’ll gain practical experience with industry tools, learn how to analyze data, and apply data-driven insights to solve problems. Whether you’re starting out or advancing your career, this certification will set you apart in the data industry.
This session provides a strong foundation in Data Science by introducing its concepts, applications, and key tools. Participants will learn how to collect, clean, and visualize data to derive meaningful insights.
What You Will Learn:
• Introduction to Data Science: Overview, career paths, and industry use cases.
• Understanding data types, structured vs. unstructured data.
• Data collection methods and sources (APIs, databases, web scraping).
• Data preprocessing techniques: handling missing values, removing duplicates.
• Data cleaning using Python libraries like Pandas.
• Introduction to data visualization using Matplotlib & Seaborn.
• Exploratory Data Analysis (EDA) techniques to summarize data insights.
Participants will learn the fundamentals of supervised learning, where models make predictions based on labeled datasets. Hands-on exercises will reinforce understanding of these models.
What You Will Learn:
• Introduction to machine learning and types of learning (supervised, unsupervised, reinforcement).
• Understanding supervised learning: how models learn from labeled data.
• Regression models (Linear Regression, Decision Trees) for continuous data prediction.
• Classification models (Logistic Regression, K-Nearest Neighbors, Decision Trees) for categorical predictions.
• Model training, validation, and performance evaluation using metrics like RMSE, accuracy, precision, and recall.
• Hands-on practice: Training a supervised learning model with real-world datasets.
Unsupervised learning models help uncover hidden patterns in data without labeled outputs. This session focuses on clustering and dimensionality reduction techniques.
What You Will Learn:
• Introduction to unsupervised learning: when and why to use it.
• Clustering algorithms: K-Means, Hierarchical Clustering, and DBSCAN.
• Dimensionality reduction techniques: PCA (Principal Component Analysis).
• Identifying relationships and patterns within unlabeled data.
• Hands-on exercise: Implementing clustering algorithms on real datasets.
This session introduces Natural Language Processing (NLP), which allows machines to understand and analyze human language.
What You Will Learn:
• Introduction to Text Analytics and NLP.
• Understanding tokenization, stemming, and lemmatization.
• Removing stopwords and cleaning text data.
• Sentiment analysis using machine learning models.
• Topic modeling techniques such as Latent Dirichlet Allocation (LDA).
• Hands-on exercises: Analyzing social media data, customer reviews, or news articles.
The final day consolidates all learning into a real-world case study, allowing participants to apply their skills and present findings.
What You Will Learn:
• Overview of a real-world Data Science problem.
• Group work or individual case study analysis.
• Building and presenting data-driven solutions.
• Receiving feedback from facilitators.
• Discussion on career paths and industry opportunities in Data Science.
Advanced-level participants will learn data processing techniques to enhance model performance and create high-quality features for machine learning models.
What You Will Learn:
• Advanced Statistical Inference: Hypothesis testing, confidence intervals.
• Feature engineering techniques: Creating, selecting, and transforming features.
• Handling imbalanced datasets with techniques like SMOTE.
• Dimensionality reduction (PCA, t-SNE) for large datasets.
• Feature scaling: Normalization vs. Standardization.
• Hands-on implementation: Applying feature engineering to datasets.
Participants will explore advanced machine learning techniques to improve model accuracy and interpretability.
What You Will Learn:
• Ensemble learning techniques: Random Forest, Gradient Boosting (XGBoost, LightGBM).
• Hyperparameter tuning methods: Grid Search, Random Search, Bayesian Optimization.
• Model evaluation techniques: AUC-ROC, Precision-Recall, Confusion Matrix.
• Explainability in Machine Learning: SHAP, LIME.
• Hands-on exercise: Implementing ensemble methods and evaluating models.
This session introduces Deep Learning and how neural networks power AI applications.
What You Will Learn:
• Introduction to Neural Networks: Perceptron, Activation Functions.
• Training Deep Learning models using TensorFlow & PyTorch.
• Convolutional Neural Networks (CNN) for image recognition tasks.
• Recurrent Neural Networks (RNN) and its variants (LSTM, GRU) for sequential data.
• Hands-on implementation: Training CNN and RNN models.
Participants will explore cutting-edge AI techniques for building high-performance deep learning models.
What You Will Learn:
• Transfer Learning: Leveraging pre-trained models (ResNet, BERT).
• Fine-tuning techniques for domain-specific tasks.
• Generative Models: GANs (Generative Adversarial Networks), VAEs (Variational Autoencoders), Transformers.
• Real-world applications: Image generation, text synthesis.
• Hands-on project: Applying Transfer Learning to a dataset.
The final session focuses on deploying AI models in production environments and managing the full Data Science pipeline.
What You Will Learn:
• Model Deployment techniques: Flask, FastAPI, Docker.
• MLOps best practices for maintaining scalable AI solutions.
• Explainable AI (XAI) techniques for improving model transparency.
• End-to-End Project: Deploying a real AI model on the web/cloud.
• Final project presentation and certification completion.
Learn with
PROGRAM SCHEDULE
When Will the
Program Begin?
The batch of CDSS will be held for 5 days in May, August, and November for Basic Level and in July for Advance Level. Don’t wait any longer to be one step ahead of the industry by becoming a certified data scientist!
Meet Our Program Facilitator
Learn data science from our
expert Data Scientist with
7 years of experience in
analytics and machine learning.
✔ Head of Analyst at Analyset AI
✔ Senior Analytics Engineer at Bunker Technologies, Singapore
✔ Graduated from College of Business Management, Sepuluh Nopember Institute of Technology
These are the countries that have officially recognized our certification.
and many more countries throughout Asia
Learn, Apply, and Get
Certified in Data Science
BASIC LEVEL
PREPARATION CLASS + EXAM
Rp10.000.000
Rp8.500.000
Get the best deals on preparation classes and tutorial sessions to increase your chances to success the exam!
ADVANCE LEVEL
PREPARATION CLASS + EXAM
Rp17.000.000
Rp15.000.000
Get the best deals on preparation classes and tutorial sessions to increase your chances to success the exam!