Online or onsite, instructor-led live Data Science training courses demonstrate through hands-on practice how to extract knowledge from data in different forms.
Data Science training is available as "online live training" or "onsite live training". Online live training (aka "remote live training") is carried out by way of an interactive, remote desktop. Onsite live Data Science trainings in Leiden can be carried out locally on customer premises or in NobleProg corporate training centers.
NobleProg -- Your Local Training Provider
Leiden
Golden Tulip/Tulip Inn Leiden Centre, Schipholweg 3, Leiden, Netherlands, 2316XB
The 4-star Golden Tulip Leiden Center is located right next to the Tulip Inn Leiden Center hotel; together they accommodate 7 stars under one roof. The hotels are ideally located with Leiden Central Station directly opposite and many motorways within easy reach. A beautiful location in the center of the historic city of Leiden full of museums and picturesque spots. Experience, enjoy and be inspired.
Golden Tulip & Tulip Inn Leiden Center have a large diversity of hotel rooms; from comfortable and modern furnished standard rooms to luxurious executive rooms. In total there are 155 rooms. Furthermore, the hotels have a renovated restaurant called "Rubens", a cozy bar / lounge and an extensive meeting & conference center.
The 6 multifunctional rooms make Golden Tulip & Tulip Inn Leiden Center the ideal location for small and medium-sized meetings. The rooms have a capacity of 4 to 100 people. The meeting rooms offer countless possibilities in terms of setup and technical facilities. Convenience, efficiency, hospitality and professionalism are paramount. All rooms have air conditioning, free wireless internet and daylight.
Until the early 19th century, fishing in Noordwijk aan Zee remained the most important form of income. Later the population started to focus more and more on tourism. More than 1 million overnight stays take place every year. Noordwijk aan Zee consists of several districts and is located on the dunes. There are various catering establishments such as hotels, entertainment centers and restaurants (also on the beach) and there is a shopping center that has a Sunday opening. Every year events take place on the boulevard around the lighthouse on the Vuurtorenplein. The municipality has a KNRM rescue station and a reformed church (1647) with pulpit from the 17th century.
Since the merger with the Noordwijkerhout municipality, the municipality consists of four centers.
Noordwijk aan Zee, traditionally a fishing village, has become a seaside resort with a long coastal strip of approximately 13 km. . Noordwijk aan Zee has two boulevards, both of which are named after a queen, Queen Wilhelmina Boulevard and Queen Astrid Boulevard.
Noordwijk-Binnen radiates the tranquility of earlier centuries in the old core. In 1992 the old village center was designated as a protected village view under the Monuments Act.
Noordwijkerhout, a village and former municipality northeast of Noordwijk..Noordwijk aan Zee is rated as the 12th richest location in the Netherlands. Beer magnate Freddy Heineken has built a villa there with the characteristic green roof.
The Two Brothers Noordwijk Beach Hotel is located on the boulevard of Noordwijk with a view of the village and the sea and has several conference rooms and training rooms that make it the perfect place for business meetings and stimulating training. Noordwijk is a 30-minute drive from Amsterdam and The Hague and only 20 minutes from Leiden.
This instructor-led, live training in Leiden (online or onsite) is aimed at beginner-level professionals who wish to understand the concept of pre-trained models and learn how to apply them to solve real-world problems without building models from scratch.
By the end of this training, participants will be able to:
Understand the concept and benefits of pre-trained models.
Explore various pre-trained model architectures and their use cases.
Fine-tune a pre-trained model for specific tasks.
Implement pre-trained models in simple machine learning projects.
This instructor-led, live training in Leiden (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 Leiden (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:
This instructor-led, live training in Leiden (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 Leiden (online or onsite) introduces the idea of collaborative development in data science and demonstrates how to use Jupyter to track and participate as a team in the "life cycle of a computational idea". It walks participants through the creation of a sample data science project based on top of the Jupyter ecosystem.
By the end of this training, participants will be able to:
Install and configure Jupyter, including the creation and integration of a team repository on Git.
Use Jupyter features such as extensions, interactive widgets, multiuser mode and more to enable project collaboraton.
Create, share and organize Jupyter Notebooks with team members.
Choose from Scala, Python, R, to write and execute code against big data systems such as Apache Spark, all through the Jupyter interface.
This instructor-led, live training in Leiden (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:
In the first part of this training, we cover the fundamentals of MATLAB and its function as both a language and a platform. Included in this discussion is an introduction to MATLAB syntax, arrays and matrices, data visualization, script development, and object-oriented principles.
In the second part, we demonstrate how to use MATLAB for data mining, machine learning and predictive analytics. To provide participants with a clear and practical perspective of MATLAB's approach and power, we draw comparisons between using MATLAB and using other tools such as spreadsheets, C, C++, and Visual Basic.
In the third part of the training, participants learn how to streamline their work by automating their data processing and report generation.
Throughout the course, participants will put into practice the ideas learned through hands-on exercises in a lab environment. By the end of the training, participants will have a thorough grasp of MATLAB's capabilities and will be able to employ it for solving real-world data science problems as well as for streamlining their work through automation.
Assessments will be conducted throughout the course to gauge progress.
Format of the Course
Course includes theoretical and practical exercises, including case discussions, sample code inspection, and hands-on implementation.
Note
Practice sessions will be based on pre-arranged sample data report templates. If you have specific requirements, please contact us to arrange.
The training course will help the participants prepare for Web Application Development using Python Programming with Data Analytics. Such data visualization is a great tool for Top Management in decision making.
Participants who complete this training will gain a practical, real-world understanding of Data Science and its related technologies, methodologies and tools.
Participants will have the opportunity to put this knowledge into practice through hands-on exercises. Group interaction and instructor feedback make up an important component of the class.
The course starts with an introduction to elemental concepts of Data Science, then progresses into the tools and methodologies used in Data Science.
Audience
Developers
Technical analysts
IT consultants
Format of the Course
Part lecture, part discussion, exercises and heavy hands-on practice
Note
To request a customized training for this course, please contact us to arrange.
Python is a programming language that has gained huge popularity in the financial industry. Adopted by the largest investment banks and hedge funds, it is being used to build a wide range of financial applications ranging from core trading programs to risk management systems.
In this instructor-led, live training, participants will learn how to use Python to develop practical applications for solving a number of specific finance related problems.
By the end of this training, participants will be able to:
Understand the fundamentals of the Python programming language
Download, install and maintain the best development tools for creating financial applications in Python
Select and utilize the most suitable Python packages and programming techniques to organize, visualize, and analyze financial data from various sources (CSV, Excel, databases, web, etc.)
Build applications that solve problems related to asset allocation, risk analysis, investment performance and more
Troubleshoot, integrate, deploy, and optimize a Python application
Audience
Developers
Analysts
Quants
Format of the course
Part lecture, part discussion, exercises and heavy hands-on practice
Note
This training aims to provide solutions for some of the principle problems faced by finance professionals. However, if you have a particular topic, tool or technique that you wish to append or elaborate further on, please please contact us to arrange.
This instructor-led, live training (online or onsite) is aimed at professionals who wish to start 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 is and how it can add value to virtually 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 Leiden (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.
Overview
Communications service providers (CSP) are facing pressure to reduce costs and maximize average revenue per user (ARPU), while ensuring an excellent customer experience, but data volumes keep growing. Global mobile data traffic will grow at a compound annual growth rate (CAGR) of 78 percent to 2016, reaching 10.8 exabytes per month.
Meanwhile, CSPs are generating large volumes of data, including call detail records (CDR), network data and customer data. Companies that fully exploit this data gain a competitive edge. According to a recent survey by The Economist Intelligence Unit, companies that use data-directed decision-making enjoy a 5-6% boost in productivity. Yet 53% of companies leverage only half of their valuable data, and one-fourth of respondents noted that vast quantities of useful data go untapped. The data volumes are so high that manual analysis is impossible, and most legacy software systems can’t keep up, resulting in valuable data being discarded or ignored.
With Big Data & Analytics’ high-speed, scalable big data software, CSPs can mine all their data for better decision making in less time. Different Big Data products and techniques provide an end-to-end software platform for collecting, preparing, analyzing and presenting insights from big data. Application areas include network performance monitoring, fraud detection, customer churn detection and credit risk analysis. Big Data & Analytics products scale to handle terabytes of data but implementation of such tools need new kind of cloud based database system like Hadoop or massive scale parallel computing processor ( KPU etc.)
This course work on Big Data BI for Telco covers all the emerging new areas in which CSPs are investing for productivity gain and opening up new business revenue stream. The course will provide a complete 360 degree over view of Big Data BI in Telco so that decision makers and managers can have a very wide and comprehensive overview of possibilities of Big Data BI in Telco for productivity and revenue gain.
Course objectives
Main objective of the course is to introduce new Big Data business intelligence techniques in 4 sectors of Telecom Business (Marketing/Sales, Network Operation, Financial operation and Customer Relation Management). Students will be introduced to following:
Introduction to Big Data-what is 4Vs (volume, velocity, variety and veracity) in Big Data- Generation, extraction and management from Telco perspective
How Big Data analytic differs from legacy data analytic
In-house justification of Big Data -Telco perspective
Introduction to Hadoop Ecosystem- familiarity with all Hadoop tools like Hive, Pig, SPARC –when and how they are used to solve Big Data problem
How Big Data is extracted to analyze for analytics tool-how Business Analysis’s can reduce their pain points of collection and analysis of data through integrated Hadoop dashboard approach
Basic introduction of Insight analytics, visualization analytics and predictive analytics for Telco
Customer Churn analytic and Big Data-how Big Data analytic can reduce customer churn and customer dissatisfaction in Telco-case studies
Network failure and service failure analytics from Network meta-data and IPDR
Financial analysis-fraud, wastage and ROI estimation from sales and operational data
Customer acquisition problem-Target marketing, customer segmentation and cross-sale from sales data
Introduction and summary of all Big Data analytic products and where they fit into Telco analytic space
Conclusion-how to take step-by-step approach to introduce Big Data Business Intelligence in your organization
Target Audience
Network operation, Financial Managers, CRM managers and top IT managers in Telco CIO office.
The explosion of information and data in today’s world is un-paralleled, our ability to innovate and push the boundaries of the possible is growing faster than it ever has. The role of Data Scientist is one of the highest in-demand skills across industry today.
We offer much more than learning through theory; we deliver practical, marketable skills that bridge the gap between the world of academia and the demands of industry.
This 7 week curriculum can be tailored to your specific Industry requirements, please contact us for further information or visit the Nobleprog Institute website
Audience:
This programme is aimed post level graduates as well as anyone with the required pre-requisite skills which will be determined by an assessment and interview.
Delivery:
Delivery of the course will be a mixture of Instructor Led Classroom and Instructor Led Online; typically the 1st week will be 'classroom led', weeks 2 - 6 'virtual classroom' and week 7 back to 'classroom led'.
Big data is data sets 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 meant for Marketing Sales Professionals who are intending to get deeper into application of data science in Marketing/ Sales. The course provides
detailed coverage of different data science techniques used for “upsale”, “cross-sale”, market segmentation, branding and CLV.
Difference of Marketing and Sales - How is that sales and marketing are different?
In very simplewords, sales can be termed as a process which focuses or targets on individuals or small groups. Marketing on the other hand targets a larger group or the general public. Marketing includes research (identifying needs of the customer), development of products (producing innovative products) and promoting the product (through advertisements) and create awareness about the product among the consumers. As such marketing means generating leads or prospects. Once the product is out in the market, it is the task of the sales person to persuade the customer to buy the product. Sales means converting the leads or prospects into purchases and orders, while marketing is aimed at longer terms, sales pertain to shorter goals.
KNIME Analytics Platform is a leading open source option for data-driven innovation, helping you discover the potential hidden in your data, mine for fresh insights, or predict new futures. With more than 1000 modules, hundreds of ready-to-run examples, a comprehensive range of integrated tools, and the widest choice of advanced algorithms available, KNIME Analytics Platform is the perfect toolbox for any data scientist and business analyst.
This course for KNIME Analytics Platform is an ideal opportunity for beginners, advanced users and KNIME experts to be introduced to KNIME, to learn how to use it more effectively, and how to create clear, comprehensive reports based on KNIME workflows
This instructor-led, live training (online or onsite) is aimed at data professionals who wish to use KNIME to solve complex business needs.
It is targeted for the audience that doesn't know programming and intends to use cutting edge tools to implement analytics scenarios
By the end of this training, participants will be able to:
Install and configure KNIME.
Build Data Science scenarios
Train, test and validate models
Implement end to end value chain of data science models
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 or to know more on this program, please contact us to arrange.
This instructor-led, live training in Leiden (online or onsite) is aimed at intermediate-level data analysts, developers, or aspiring data scientists who wish to apply machine learning techniques in Python to extract insights, make predictions, and automate data-driven decisions.By the end of this course, participants will be able to:
Understand and differentiate key machine learning paradigms.
Explore data preprocessing techniques and model evaluation metrics.
Apply machine learning algorithms to solve real-world data problems.
Use Python libraries and Jupyter notebooks for hands-on development.
Build models for prediction, classification, recommendation, and clustering.
This instructor-led, live training in Leiden (online or onsite) is aimed at data analysts and web developers who wish to develop associative models in Qlik Sense.
By the end of this training, participants will be able to:
Apply Qlik Sense in data science.
Use and navigate the Qlik Sense interface.
Build a data literate workforce with AI interaction.
Practical Quantum Computing: Live Online
Launch your high-tech career
This is a 10 hour instructor-led, live online training course. After your immersive training, you will be ready to start work as an entry level quantum computing developer.
By the end of this training, participants will be able to:
Run and test your quantum programs with the integrated IBM Q
Use Qiskit to create, compile, and execute quantum computing programs
Working with practical and advanced quantum algorithms such as QAOA
Recast real-world problems into an appropriate quantum computing language
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 Leiden (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.
This instructor-led, live training in Leiden (online or onsite) is aimed at data scientists who wish to use the SMACK stack to build data processing platforms for big data solutions.
By the end of this training, participants will be able to:
Implement a data pipeline architecture for processing big data.
Develop a cluster infrastructure with Apache Mesos and Docker.
This instructor-led, live training in Leiden (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.
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Testimonials (8)
Understanding big data beter
Shaune Dennis - Vodacom
Course - Big Data Business Intelligence for Telecom and Communication Service Providers
very interactive...
Richard Langford
Course - SMACK Stack for Data Science
Younes is a great trainer. Always willing to assist, and very patient. I will give him 5 stars. Also, the QLIK sense training was excellent, due to an excellent trainer.
Dietmar Glanninger - BMW
Course - Qlik Sense for Data Science
Trainer was accommodative. And actually quite encouraging for me to take up the course.
Grace Goh - DBS Bank Ltd
Course - Python in Data Science
Subject presentation knowledge timing
Aly Saleh - FAB banak Egypt
Course - Introduction to Data Science and AI (using Python)
It is great to have the course custom made to the key areas that I have highlighted in the pre-course questionnaire. This really helps to address the questions that I have with the subject matter and to align with my learning goals.
Winnie Chan - Statistics Canada
Course - Jupyter for Data Science Teams
It is showing many methods with pre prepared scripts- very nicely prepared materials & easy to traceback
Kamila Begej - GE Medical Systems Polska Sp. Zoo
Course - Machine Learning – Data science
The example and training material were sufficient and made it easy to understand what you are doing.
Teboho Makenete
Course - Data Science for Big Data Analytics
Provisional Upcoming Courses (Contact Us For More Information)
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