Jupyter for Data Science Teams Training Course

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

The course includes practical examples and exercises using Python.

This instructor-led, live training in Serbia (online or onsite) is aimed at intermediate-level participants who wish to automate and manage machine learning workflows, including model training, validation, and deployment using 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 Serbia (online or onsite) is aimed at data scientists who wish to use the Anaconda ecosystem to capture, manage, and deploy packages and data analysis workflows in 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.
• Get to know some practical use cases and techniques for managing multiple data environments.

This instructor-led, live training in Serbia (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 Serbia (online or onsite) is aimed at 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.

This is an ideal introduction to data science for managers, giving you the chance to learn about this powerful business tool.

Participants who complete this training will acquire a practical, real-world understanding of Data Science and its associated technologies, methodologies, and tools.

They will have the chance to apply this knowledge through hands-on exercises. Group interaction and instructor feedback are integral components of the class.

The course begins with an introduction to fundamental concepts of Data Science and then advances into the tools and methodologies used in the field.

Audience

• Developers
• Technical Analysts
• IT Consultants

Format of the Course

• The course combines lectures, discussions, exercises, and extensive hands-on practice.

Note

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

The unprecedented growth of information and data in today’s world is driving rapid innovation and expanding the boundaries of what is possible. The role of a Data Scientist is one of the most sought-after skills across industries today.

We offer more than just theoretical learning; we provide practical, marketable skills that bridge the gap between academic knowledge and industry demands.

This 7-week curriculum can be customized to meet your specific industry needs. For further information or to visit the Nobleprog Institute website, please contact us.

Audience:

This program is designed for postgraduate students as well as anyone who possesses the necessary pre-requisite skills, which will be assessed through an evaluation and interview process.

Delivery:

The course delivery will combine Instructor-Led Classroom sessions and Instructor-Led Online sessions. Typically, the first week will be classroom-based, weeks 2 to 6 will be virtual classroom sessions, and the final week will return to a classroom setting.

Big data refers to data sets that are so large and intricate that conventional data processing applications struggle to manage them effectively. The challenges associated with big data encompass various aspects such as data capture, storage, analysis, search, sharing, transfer, visualization, querying, updating, and ensuring information privacy.

This course is designed for Marketing Sales Professionals who aim to delve deeper into the application of data science in Marketing and Sales. The course offers comprehensive coverage of various data science techniques used for upselling, cross-selling, market segmentation, branding, and customer lifetime value (CLV).

Difference Between Marketing and Sales - How do sales and marketing differ?

In simple terms, sales can be described as a process that focuses on individuals or small groups. On the other hand, marketing targets a broader audience or the general public. Marketing encompasses research (identifying customer needs), product development (creating innovative products), and promotion (advertising to create awareness among consumers). Essentially, marketing is about generating leads or prospects. Once the product is available in the market, it is the salesperson's role to persuade customers to make a purchase. While sales focus on converting leads into actual purchases and orders, marketing has a longer-term perspective.

This instructor-led, live training (online or onsite) is designed for professionals looking to embark on a career in Data Science.

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

• Install and configure Python and MySQL.
• Understand what Data Science entails and how it can bring value to almost any business.
• Learn the basics of coding in Python.
• Explore supervised and unsupervised Machine Learning techniques, and gain hands-on experience in implementing them and interpreting the results.

Format of the Course

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

Course Customization Options

• For customized training options, please contact us to arrange.

This instructor-led, live training in Serbia (online or onsite) is aimed at 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:

• Learn about data science and machine learning.
• Explore data analytics.
• Learn about Kaggle and how it works.

KNIME Analytics Platform stands out as a top open-source solution for data-driven innovation, empowering you to uncover the hidden potential in your data, discover new insights, and predict future outcomes. With over 1,000 modules, hundreds of ready-to-use examples, an extensive array of integrated tools, and a wide selection of advanced algorithms, KNIME Analytics Platform is the ideal toolkit for any data scientist or business analyst.

This course on KNIME Analytics Platform offers a perfect opportunity for beginners, advanced users, and KNIME experts to familiarize themselves with KNIME, learn how to use it more effectively, and create clear and comprehensive reports based on KNIME workflows.

This instructor-led, live training (available online or onsite) is designed for data professionals who want to leverage KNIME to address complex business requirements.

It is particularly suitable for those without programming knowledge but who intend to use state-of-the-art tools to implement analytics scenarios.

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

• Install and configure KNIME.
• Develop data science scenarios.
• Train, test, and validate models.
• Implement the full value chain of data science models from start to finish.

Format of the Course

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

Course Customization Options

• To request a customized training for this course or to learn more about the program, please contact us to arrange.

This instructor-led, live training in Serbia (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 instructor-led, live training in Serbia (online or onsite) is aimed at 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, cuML, etc.

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.