Course Overview:

Data science enables organizations to extract insights from data, driving smarter decisions and better customer experiences. This course teaches participants how to accelerate data science workflows using GPU-powered tools. From data analysis to machine learning deployment, learners will explore a complete pipeline using RAPIDS libraries and Triton Inference Server. The course includes a hands-on simulation to analyze and prevent a hypothetical epidemic outbreak in the UK, showcasing real-world applications of accelerated data science. 

After completing this course, participants will be able to:

  • Use cuDF to accelerate pandas, Polars, and Dask for efficient data analysis.
  • Apply machine learning algorithms like XGBoost to solve diverse data science problems.
  • Deploy models using Triton Inference Server for optimal performance.
  • Analyze complex networks using graph algorithms with NetworkX and cuGraph.
  • Perform large-scale analysis tasks on massive datasets.

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Key Features:

  • Hands-on labs using RAPIDS and GPU-accelerated libraries.

  • Real-world epidemic simulation project.

  • Tools like cuDF, cuML, cuGraph, Dask, and Triton.

  • Intermediate-level technical training.

  • Certificate of completion from NVIDIA DLI.

Who should Attend?

  • Data scientists and analysts
  • Machine learning engineers
  • Developers working on scalable data pipelines
  • Professionals seeking to optimize data science workflows

Prerequisites:

  • Experience with Python, including pandas and NumPy
  • Suggested resources: Kaggle’s pandas’ tutorials, Kaggle’s Intro to Machine Learning, Accelerating Data Science Workflows with RAPIDS

    • Why choose CloudThat as your training partner?

    • Specialized Data Science Focus: CloudThat offers expert-led training designed specifically for modern data science workflows, emphasizing GPU acceleration and scalable solutions.
    • Industry-Recognized Trainers: Our instructors are certified professionals with hands-on experience in RAPIDS, XGBoost, cuDF, and other cutting-edge tools used in enterprise data science.
    • Hands-On Learning Approach: Learners engage in practical labs and simulations, including real-world projects like epidemic outbreak analysis using massive datasets.
    • Customized Learning Paths: Whether you're a data analyst, ML engineer, or transitioning into data science, our training adapts to your background and goals.
    • Interactive Learning Experience: Participate in live sessions, Q&A, and mentorship that make complex data science concepts accessible and actionable.
    • Placement Assistance and Career Support: We help learners with resume building, interview preparation, and job placement opportunities in data science and AI roles.
    • Continuous Learning and Updates: Our curriculum is regularly updated to reflect the latest trends and tools in accelerated data science and machine learning.
    • Positive Reviews and Testimonials: Trusted by thousands of learners and top enterprises, CloudThat is known for delivering impactful and career-oriented training.

    Course Outline: Download Course Outline

    • Efficient handling of large datasets

    • Training and evaluating models

    • Serving models for real-time inference

    • Analyzing complex networks

    • Applying learned techniques to a real-world scenario

    Certification Details:

      Participants who complete the course and hands-on labs will receive an official NVIDIA Deep Learning Institute Certificate of Completion for Accelerating End-to-End Data Science Workflows.

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    Course ID: 26358

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    FAQs:

    Yes, basic experience with Python and libraries like pandas and NumPy is recommended.

    The course uses RAPIDS, cuDF, cuML, cuGraph, Dask, Triton Inference Server, and more.

    Yes, upon successful completion, you will receive an NVIDIA DLI Certificate of Completion.

    This course supports roles in data science, ML engineering, and AI infrastructure optimization.

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