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 training can be carried out locally on customer premises in Georgia or in NobleProg corporate training centers in Georgia.
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Atlanta, GA – Regus at Colony Squar
1201 Peachtree Street NE, Suite 200, Atlanta, United States, 30361
The venue is centrally located in Midtown Atlanta within the prominent Colony Square complex at 1201 Peachtree Street NE, easily accessed by car via I‑75/85 or GA‑400, with several parking garages nearby. From Hartsfield–Jackson Atlanta International Airport (ATL), around 15 miles south, a taxi or rideshare typically takes 20–30 minutes north along I‑75/85 N. Public transit users can take MARTA Rail to the Arts Center or Midtown stations (0.3–0.5 miles away) and walk easily, and numerous MARTA bus routes along Peachtree Street stop directly outside the entrance.
Atlanta, GA – The Proscenium
1170 Peachtree Street NE, Atlanta, United States, 30309
The venue is located in the heart of Midtown Atlanta in the Proscenium high–rise at 1170 Peachtree Street NE, easily accessible by car via I‑75/85 and GA‑400 with several parking garages nearby. Visitors arriving from Hartsfield–Jackson Atlanta International Airport (ATL), about 15 miles south, can expect a taxi or rideshare ride taking 20–30 minutes via I‑75/85 North. Public transit is seamless with MARTA Rail service; the Arts Center and Midtown stations are within walking distance (approximately 0.3–0.4 miles), and multiple MARTA bus routes also serve Peachtree Street.
Decatur, GA – Regus at One West Court Square
One West Court Square, Suite 750, Decatur, United States, 30030
The venue is located in the heart of downtown Decatur within One West Court Square, easily reached by car via I‑20 and I‑285, with several public parking decks directly adjacent. Travelers from Hartsfield–Jackson Atlanta International Airport (ATL), approximately 17 miles southwest, can expect a taxi or rideshare ride of around 25–30 minutes via I‑20 East. Public transit is particularly convenient: MARTA rail users can disembark at Decatur Station (about 0.15 miles away) and walk a few minutes to the building entrance. Local bus routes also serve Trinity Place and Swanton Way, putting the center within easy reach.
Atlanta, GA – Regus at One Hartsfield
100 Hartsfield Centre Parkway, Suite 500, Atlanta, United States, 30354
The venue is located in the One Hartsfield Center office building, adjacent to Hartsfield–Jackson Atlanta International Airport, easily reached by car via I‑75/I‑85 or GA‑138, with abundant on-site parking. Visitors arriving from ATL airport can walk or take a shuttle to the building, or opt for a quick 2–3‑minute taxi or rideshare ride. Public transit users can board MARTA from the Airport Station and ride one stop to College Park Station, then catch a connecting shuttle or enjoy a brief walk of about half a mile.
Atlanta, GA – Regus at Peachtree
260 Peachtree Street NW, Suite 2200, Atlanta, United States, 30303
The venue is situated in the iconic Coastal States Building at 260 Peachtree Street in downtown Atlanta, accessible by car via I‑75/85 or I‑20 with convenient parking garages nearby. From Hartsfield–Jackson Atlanta International Airport (ATL), about 12 miles south, a taxi or rideshare along I‑75/85 North takes approximately 15–20 minutes. For public transit, MARTA rail users can disembark at Five Points Station and walk 0.5 miles northeast, or exit at Peachtree Center Station and walk two blocks north—both routes offering easy access.
Augusta, GA – At Broad Street
823 Broad Street, Augusta, United States, 3090
The venue is located in the heart of downtown Augusta on Broad Street, easily accessible by car via I‑20 with several public parking garages nearby. From Augusta Regional Airport (AGS), about 9 miles west, taxis or rideshares typically take 15–20 minutes via I‑20. Public transit is available through Augusta Public Transit buses with routes along Broad Street, stopping within a few blocks of the venue, offering a convenient option for attendees without a car.
Savannah, GA – Regus at Bull Street
100 Bull St Downtown, Suite 200, Savannah, United States, 31401
The venue is located in the historic downtown area on Bull Street in the Altmayer Building, easily accessible by car via I‑16 and U.S. 17, with several public garages nearby. From Savannah/Hilton Head International Airport (SAV), about 12 miles west, taxis or rideshares typically take 15–20 minutes via U.S. 17 South. Public transit is available via Chatham Area Transit (CAT) buses, with frequent service along Bull and Broughton Streets; Johnson Square Station is just a couple minutes’ walk from the venue.
This instructor-led, live training in Georgia (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 Georgia (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 Georgia (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 Georgia (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 Georgia (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 Georgia (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 in Georgia (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.
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 Georgia (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 Georgia (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.
This instructor-led, live training in Georgia (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 Georgia (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 Georgia (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 (7)
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.
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