SMACK Stack for Data Science Training Course

This is a 5-day introductory course covering Data Science and Artificial Intelligence (AI).

The course is delivered with examples and exercises using Python

This live, instructor-led training held in the UAE (online or onsite) is designed for intermediate-level participants who wish to automate and manage machine learning workflows, encompassing model training, validation, and deployment via Apache Airflow.

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

• Set up Apache Airflow for machine learning workflow orchestration.
• Automate data preprocessing, model training, and validation tasks.
• Integrate Airflow with machine learning frameworks and tools.
• Deploy machine learning models using automated pipelines.
• Monitor and optimize machine learning workflows in production.

This instructor-led, live training in the UAE (online or onsite) is designed for data scientists aiming to leverage the Anaconda ecosystem to capture, manage, and deploy packages and data analysis workflows in a unified platform.

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

• Install and configure Anaconda components and libraries.
• Comprehend the core concepts, features, and advantages of Anaconda.
• Manage packages, environments, and channels using Anaconda Navigator.
• Utilize Conda, R, and Python packages for data science and machine learning applications.
• Explore practical use cases and techniques for managing multiple data environments.

This instructor-led, live training in the UAE (online or on-site) 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 the UAE (online or onsite) is targeted at beginner-level data scientists and IT professionals who intend to learn the basics of data science using Google Colab.

By the conclusion 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.

This course serves as an ideal introduction to data science for managers, offering a valuable opportunity to master this powerful business tool.

Upon completing this training, participants will acquire a hands-on, real-world comprehension of Data Science, along with its associated technologies, methodologies, and tools.

Learners will have the chance to apply their new knowledge through practical exercises. The course emphasizes group interaction and valuable feedback from the instructor as key components of the learning experience.

The curriculum begins by introducing 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 intensive hands-on practice

Note

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

Big data refers to datasets that are excessively large and complex, rendering traditional data processing software inadequate. The challenges associated with big data encompass data capture, storage, analysis, search, sharing, transfer, visualization, querying, updating, and information privacy.

This course is designed for marketing and sales professionals aiming to deepen their expertise in applying data science methodologies to these fields. It provides comprehensive coverage of various data science techniques utilized for upselling, cross-selling, market segmentation, branding, and Customer Lifetime Value (CLV).\n

The Distinction Between Marketing and Sales - What sets them apart?

In simple terms, sales targets individuals or small groups, whereas marketing addresses a broader audience or the general public. Marketing involves research to identify customer needs, product development for innovation, and promotion through advertising to build awareness. Essentially, marketing generates leads and prospects. Once a product is launched, the salesperson's role is to persuade these prospects to make a purchase. Thus, sales focuses on converting leads into orders with short-term goals, while marketing is oriented toward long-term strategy.

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

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

• Gain a solid understanding of data science and machine learning principles.
• Analyze data using advanced analytics techniques.
• Familiarize themselves with the Kaggle platform and its operational mechanisms.

This instructor-led, live training in the UAE (online or onsite) is designed for 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 constructing scalable data processing and Machine Learning workflows using PySpark. Participants will gain insights into how Apache Spark functions within contemporary Big Data ecosystems and learn to process large datasets efficiently by leveraging distributed computing principles.

This instructor-led, live training in the UAE (online or onsite) is designed 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.

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

• Configure the required development environment to build data models using NVIDIA RAPIDS.
• Gain a comprehensive understanding of RAPIDS' features, components, and benefits.
• Utilize GPUs to speed up end-to-end data and analytics pipelines.
• Implement GPU-accelerated data preparation and ETL processes using cuDF and Apache Arrow.
• Master the execution of machine learning tasks using XGBoost and cuML algorithms.
• Create data visualizations and perform graph analysis with cuXfilter and cuGraph.

In this instructor-led, live training in the UAE, participants will learn how to use Python and Spark together to analyze big data as they work on 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 serves as a comprehensive, data-centric platform that unifies big data, artificial intelligence, and governance into a single solution. Its Rocket and Intelligence modules facilitate rapid data exploration, transformation, and advanced analytics within enterprise settings.

This instructor-led live training (available online or on-site) targets intermediate-level data professionals aiming to leverage the Rocket and Intelligence modules in Stratio effectively with PySpark. The curriculum focuses on looping structures, user-defined functions, and advanced data logic.

Upon completion of this training, participants will be capable of:

• Navigating and operating within the Stratio platform using the Rocket and Intelligence modules.
• Applying PySpark for data ingestion, transformation, and analysis.
• Utilizing loops and conditional logic to manage data workflows and feature engineering tasks.
• Creating and managing user-defined functions (UDFs) for reusable data operations in PySpark.

Course Format

• Interactive lectures and discussions.
• Extensive exercises and practical sessions.
• Hands-on implementation in a live lab environment.

Customization Options

• To request customized training for this course, please contact us to make arrangements.