TRAINING COURSE

Integration of Neural Networks in Big Data Analysis:

New Approaches and Applications

STARTING TWICE A MONTH
DURATION 7 WEEKS
‎‎ ‎8 100 €
For those interested in applying Neural Networks (NNs) to better analyze and utilize Big Data. Participants will gain in-depth knowledge of the latest NN approaches and applications in the context of Big Data Analytics, enabling them to more effectively solve complex problems in their field.
Deep understanding of the structures and functions of NNs
Skills in processing and analyzing Big Data using NNs.
Practical application of NNs to solve problems in the field of Big Data Analysis.
Training Course Program
STARTING TWICE A MONTH
Lecture 1:
Foundations of Neural Networks in Big Data: Unveiling the Power of Analysis
  • Introduction to Big Data Analytics (BDA) and NNs
  • Introduction to BDA and its significance
  • Fundamentals of NNs and their application in data analysis
  • Examples of successful NN applications in BDA
Lecture 2:
Machine Learning Marvels: Navigating Big Data Terrain with Neural Networks
  • Basics of Machine Learning (ML) algorithms for Big Data
  • Key methods for processing large volumes of data
  • Overview of ML algorithms used in BDA
  • Various approaches to processing Big Data using NNs
Lecture 3:
Deep Dive into Big Data: Harnessing the Power of Deep Learning
  • Deep Learning (DL) and its application in BDA
  • Immersion into the concept of DL
  • Application of DL in BDA
  • Examples of using DL to solve BDA tasks
Lecture 4:
Neural Networks Unleashed: Transforming Text and Images in Big Data Analytics
  • Application of NNs in text and image processing
  • Utilizing NNs for text data analysis
  • Application of NNs in image processing and pattern recognition
  • Practical examples and demonstrations of using NNs in text and image processing
Lecture 5:
Neural Network Architectures: Designing the Future of Big Data Processing
  • Architectures of NNs for Big Data processing
  • Overview of different NN architectures for BDA
  • Exploring the specifics of various architectures and their applicability to specific tasks
  • Comparing the performance of different architectures in the context of Big Data processing
Lecture 6:
Neural Networks Optimization for Big Data Excellence
  • Techniques for optimizing NNs in Big Data processing
  • Key methods for optimizing the performance of NNs when dealing with large datasets
  • Approaches to accelerate learning and prediction using NNs
  • Optimizing performance when working with large datasets
Lecture 7:
Predictive Power: Neural Networks in Big Data Forecasting and Analytics
  • Application of NNs in Big Data forecasting and analytics
  • The role of NNs in forecasting and analytics for Big Data
  • Using NNs to forecast trends and patterns in large datasets
  • Case studies and real-world examples of using NNs in Big Data forecasting
Lecture 8:
Ethics and Compliance: Navigating Neural Networks in Big Data Analytics
  • Ethical and legal aspects of NN use in BDA
  • Ethical considerations in using NNs for processing and analyzing Big Data
  • Legal constraints and norms when employing NNs in BDA
  • Recommendations for ethical and lawful application of NNs in BDA
Practical Session 1:
Hands-On Applications: Putting Neural Networks into Practice with Big Data
  • Introduction to programming NNs for BDA
  • Basic principles of programming NNs for BDA
  • Work with popular DL libraries such as TensorFlow or PyTorch and create a simple NN for analyzing a small dataset
  • Fundamentals of training, testing, and evaluating model performance on various metrics
Practical Session 2:
Neural Networks Mastery: Text and Image Processing Development Session
  • Development of NN models for text and image processing
  • Study of methods for developing NNs for text and image processing
  • Work with real-world datasets, applying knowledge to create and train NN models for text and image classification
  • Data preprocessing techniques, including text vectorization and image enhancement
Practical Session 3:
Maximizing Neural Networks: Strategies for Large Data Optimization Session
  • Optimization of NN performance for handling large data
  • Participants will explore various methods for optimizing the performance of NNs when dealing with large datasets
  • Methods for parallelizing NN training, optimizing model architecture, and improving memory efficiency
  • Students will apply these techniques to their own models, measuring and comparing performance before and after optimization
Practical Session 4:
Real-World Mastery: Applying Neural Networks to Analyze Big Data Sets
  • Practical examples of applying NNs in analyzing real Big Data sets
  • Applying the acquired knowledge in practice
  • Designing and tuning NNs for specific data analysis tasks such as trend prediction, classification or clustering
  • Apply programming and data analysis skills to create innovative solutions based on NNs
What kind of result will you get
Participants in this course will acquire in-depth knowledge of NN applications in BDA. They will master key methods of data processing and optimization, develop and modify NN models for text and images, and learn to apply them to real data analysis problems. Upon completion of the course, participants will possess not only theoretical knowledge, but also practical skills that will enable them to successfully apply NNs in complex Big Data processing tasks, as well as to realize this knowledge in innovative projects.
Student feedback on the course
An excellent blend of theory and practice. Now I feel more confident in developing and optimizing neural networks for big data analytics.
Henrik Andersson
Thanks to this course, I deepened my knowledge of applying neural networks in big data analysis. Real projects and excellent instructors made the learning engaging and valuable.
Isabella De Luca
The course is well-structured, and each lecture has practical applications. I learned how to optimize the performance of neural networks when working with extensive data.
Elena Kovačić
Real examples and assignments helped me not only understand the theory but also directly apply knowledge to working with data. An excellent course for data analysis professionals!
Antonio Morelli
A very informative and interesting course! I now feel more confident working with neural networks in processing big data. Thanks for the excellent learning experience!
Sophie Lefèvre
What you will get after the course
  1. In-depth knowledge of the principles and functions of NNs and their application in various BDA scenarios.
  2. Techniques for optimizing the performance of NNs when dealing with large amounts of data, including parallelization of training, architecture optimization, and memory efficiency.
  3. Mastering the application of NNs to text and image processing, including the creation and optimization of models for text and image classification.
  4. Apply the knowledge gained on real-world data by creating and refining NNs for prediction, classification, and clustering tasks.
  5. Familiarization with relevant legislation to ensure the legitimate and ethical application of the skills learned.
Official school certificate
Recordings of all lectures
10% discount on any of our courses
Price without discount 9 000 €
8 100 €
Course fees
If you register early (over a month prior to the beginning of the course), you will receive a 10% discount on the entire program.
Register for the course and get 10% off!
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"Cosmopolitacademy" LLC
264.110.1320023
TIN: 08256519
Komitas 19/1, Erevan, Armenia