SMACK Stack for Data Science Training Course

This five-day program introduces participants to Data Science and Artificial Intelligence (AI).

Instruction is delivered through practical examples and exercises conducted in Python.

This instructor-led live training in Taiwan (available online or onsite) is designed for intermediate-level participants who wish to automate and manage machine learning workflows, including model training, validation, and deployment using Apache Airflow.

Upon completing this training, participants will be capable of:

• Configuring Apache Airflow to orchestrate machine learning workflows.
• Automating tasks such as data preprocessing, model training, and validation.
• Integrating Airflow with various machine learning frameworks and tools.
• Deploying machine learning models through automated pipelines.
• Monitoring and optimizing machine learning workflows in production environments.

This instructor-led live training, conducted in Taiwan (online or onsite), targets data scientists who wish to utilize the Anaconda ecosystem to capture, manage, and deploy packages and data analysis workflows on a single platform.

By the end of this training, participants will be able to:

• Install and configure Anaconda components and libraries.
• Understand the core concepts, features, and benefits of Anaconda.
• Manage packages, environments, and channels using Anaconda Navigator.
• Use Conda, R, and Python packages for data science and machine learning.
• Gain insight into practical use cases and techniques for managing multiple data environments.

This instructor-led, live training in Taiwan (online or onsite) is aimed at intermediate-level data scientists and analysts who wish to use AWS Cloud9 for streamlined data science workflows.

By the end of this training, participants will be able to:

• Set up a data science environment in AWS Cloud9.
• Perform data analysis using Python, R, and Jupyter Notebook in Cloud9.
• Integrate AWS Cloud9 with AWS data services like S3, RDS, and Redshift.
• Utilize AWS Cloud9 for machine learning model development and deployment.
• Optimize cloud-based workflows for data analysis and processing.

This instructor-led live training in Taiwan (online or onsite) targets beginner-level data scientists and IT professionals who wish to learn the basics of data science using Google Colab.

By the end of this training, participants will be able to:

• Set up and navigate Google Colab.
• Write and execute basic Python code.
• Import and handle datasets.
• Create visualizations using Python libraries.

Upon completing this training, participants will develop a practical, real-world grasp of Data Science, including its associated technologies, methodologies, and tools.

Attendees will apply their knowledge through interactive, hands-on exercises. The course places significant emphasis on group collaboration and direct feedback from the instructor.

The curriculum begins by covering the foundational concepts of Data Science before advancing to the specific tools and methodologies employed in the field.

Target Audience

• Developers
• Technical analysts
• IT consultants

Course Format

• A blend of lectures, discussions, exercises, and extensive hands-on practice

Important Note

• To arrange customized training for this course, please contact us.

Big data refers to datasets that are so voluminous and complex that traditional data processing application software are inadequate to deal with them. Big data challenges include capturing data, data storage, data analysis, search, sharing, transfer, visualization, querying, updating and information privacy.

This course is designed for Marketing and Sales professionals seeking to deepen their understanding of applying data science within these fields. It offers a comprehensive overview of various data science techniques utilized for "upselling," "cross-selling," market segmentation, branding, and Customer Lifetime Value (CLV).

The Distinction Between Marketing and Sales - What sets sales and marketing apart?

In simple terms, sales is a process that targets individuals or small groups. Marketing, on the other hand, aims at a broader audience or the general public. Marketing involves research (identifying customer needs), product development (creating innovative offerings), and promotion (via advertisements) to build consumer awareness. Essentially, marketing is about generating leads or prospects. Once a product reaches the market, it becomes the salesperson's role to persuade customers to make a purchase. Sales focuses on converting those leads into orders, whereas marketing is oriented toward long-term goals, while sales pertains to shorter-term objectives.

This instructor-led, live training (available online or onsite) is designed for professionals seeking to launch a career in Data Science.

By the end of this training, participants will be able to:

• Install and configure Python and MySQL.
• Understand the concept of Data Science and its value addition to almost any business.
• Learn the fundamentals of coding in Python
• Learn supervised and unsupervised Machine Learning techniques, and how to implement them and interpret the results.

Format of the Course

• Interactive lecture and discussion.
• Lots of exercises and practice.
• Hands-on implementation in a live-lab environment.

Course Customization Options

• To request a customized training for this course, please contact us to arrange.

This instructor-led live training in Taiwan (online or on-site) is designed for data scientists and developers who wish to learn and build their careers in Data Science using Kaggle.

Upon completion of this training, participants will be able to:

• Gain a comprehensive understanding of data science and machine learning.
• Explore the intricacies of data analytics.
• Understand Kaggle and its operational mechanisms.

This instructor-led, live training in Taiwan (online or onsite) is aimed at data scientists and developers who wish to use Modin to build and implement parallel computations with Pandas for faster data analysis.

By the end of this training, participants will be able to:

• Set up the necessary environment to start developing Pandas workflows at scale with Modin.
• Understand the features, architecture, and advantages of Modin.
• Know the differences between Modin, Dask, and Ray.
• Perform Pandas operations faster with Modin.
• Implement the entire Pandas API and functions.

This training offers a hands-on introduction to developing scalable data processing and Machine Learning workflows using PySpark. Participants will gain insight into how Apache Spark functions within contemporary Big Data ecosystems and learn to process extensive datasets efficiently by applying distributed computing principles.

This instructor-led, live training in Taiwan (online or onsite) is tailored for data scientists and developers who wish to use RAPIDS to build GPU-accelerated data pipelines, workflows, and visualizations, applying machine learning algorithms such as XGBoost and cuML.

By the end of this training, participants will be able to:

• Set up the necessary development environment to build data models with NVIDIA RAPIDS.
• Understand the features, components, and advantages of RAPIDS.
• Leverage GPUs to accelerate end-to-end data and analytics pipelines.
• Implement GPU-accelerated data preparation and ETL with cuDF and Apache Arrow.
• Learn how to perform machine learning tasks with XGBoost and cuML algorithms.
• Build data visualizations and execute graph analysis with cuXfilter and cuGraph.

In this instructor-led, live training in Taiwan, participants will learn how to combine Python and Spark to analyze big data through hands-on exercises.

By the end of this training, participants will be able to:

• Learn how to use Spark with Python to analyze Big Data.
• Work on exercises that mimic real world cases.
• Use different tools and techniques for big data analysis using PySpark.

Stratio is a data-centric platform that integrates big data, AI, and governance into a single solution. Its Rocket and Intelligence modules enable rapid data exploration, transformation, and advanced analytics in enterprise environments.

This instructor-led, live training (online or onsite) is aimed at intermediate-level data professionals who wish to use the Rocket and Intelligence modules in Stratio effectively with PySpark, focusing on looping structures, user-defined functions, and advanced data logic.

By the end of this training, participants will be able to:

• Navigate and work within the Stratio platform using Rocket and Intelligence modules.
• Apply PySpark in the context of data ingestion, transformation, and analysis.
• Use loops and conditional logic to control data workflows and feature engineering tasks.
• Create and manage user-defined functions (UDFs) for reusable data operations in PySpark.

Format of the Course

• Interactive lecture and discussion.
• Lots of exercises and practice.
• Hands-on implementation in a live-lab environment.

Course Customization Options

• To request a customized training for this course, please contact us to arrange.