Natural Language Processing (nlp) For Big Data Training Course: Text Data Insights

Introduction

Unlock the power of text data with our Natural Language Processing (NLP) for Big Data Training Course. This program is designed to equip you with the essential skills to extract insights from text data using advanced NLP techniques. In today's information-rich world, the ability to process and analyze vast amounts of text data is crucial for gaining valuable insights and driving informed decisions. Our NLP training course provides hands-on experience and expert guidance, empowering you to build sophisticated text analysis solutions.

This Big Data NLP training delves into the core concepts of natural language processing, covering topics such as text preprocessing, sentiment analysis, topic modeling, and information extraction. You'll gain expertise in using industry-standard tools and techniques to build NLP applications that handle the complexities of big data. Whether you're a data scientist, analyst, or engineer, this NLP for Big Data course will empower you to leverage the full potential of your text data.

Target Audience:

• Data Scientists
• Data Analysts
• Machine Learning Engineers
• Big Data Engineers
• Software Developers
• Business Intelligence Professionals
• Anyone needing NLP skills for text data analysis

Course Objectives:

• Understand the fundamentals of Natural Language Processing (NLP).
• Master text preprocessing techniques for big data.
• Implement sentiment analysis and opinion mining.
• Utilize topic modeling for text data clustering.
• Develop information extraction systems for structured data.
• Apply machine learning algorithms to NLP tasks.
• Deploy NLP models for real-world applications.
• Troubleshoot and debug NLP pipelines.
• Implement data security and access control in NLP workflows.
• Integrate NLP models with big data platforms.
• Understand how to monitor and maintain NLP models.
• Explore advanced NLP techniques for large datasets.
• Apply real world use cases for NLP in Big Data.

Duration

10 Days

Course content

Module 1: Introduction to Natural Language Processing (NLP)

• Fundamentals of NLP and text data analysis.
• Overview of NLP techniques and applications.
• Setting up a development environment for NLP.
• Introduction to NLP tools and libraries.
• Best practices for NLP.

Module 2: Text Preprocessing for Big Data

• Tokenization and text cleaning techniques.
• Stop word removal and stemming/lemmatization.
• Handling large text datasets efficiently.
• Regular expressions and pattern matching.
• Best practices for text preprocessing.

Module 3: Sentiment Analysis and Opinion Mining

• Implementing sentiment analysis algorithms.
• Utilizing lexicon-based and machine learning approaches.
• Analyzing customer reviews and social media data.
• Extracting opinions and emotions from text.
• Best practices for sentiment analysis.

Module 4: Topic Modeling for Text Data Clustering

• Implementing Latent Dirichlet Allocation (LDA).
• Utilizing Non-negative Matrix Factorization (NMF).
• Discovering hidden topics in large text datasets.
• Visualizing and interpreting topic models.
• Best practices for topic modeling.

Module 5: Information Extraction from Text

• Implementing named entity recognition (NER).
• Utilizing part-of-speech (POS) tagging.
• Extracting relations and events from text.
• Building knowledge graphs from text data.
• Best practices for information extraction.

Module 6: Machine Learning for NLP Tasks

• Applying classification algorithms for text categorization.
• Utilizing sequence models for text generation.
• Implementing word embeddings (Word2Vec, GloVe).
• Utilizing transformer models (BERT, GPT).
• Best practices for machine learning in NLP.

Module 7: NLP Model Deployment and Productionization

• Deploying NLP models in production environments.
• Utilizing containerization and orchestration tools.
• Implementing API endpoints for NLP services.
• Monitoring model performance in production.
• Best practices for model deployment.

Module 8: Troubleshooting and Debugging NLP Pipelines

• Debugging NLP models and pipelines.
• Analyzing model errors and performance issues.
• Utilizing debugging tools and techniques.
• Identifying and resolving model biases.
• Best practices for model troubleshooting.

Module 9: Data Security and Access Control in NLP

• Implementing data security in NLP workflows.
• Utilizing authentication and authorization.
• Implementing data encryption and masking.
• Auditing and compliance in NLP.
• Best practices for data security.

Module 10: Integrating NLP Models with Big Data Platforms

• Integrating NLP models with Hadoop and Spark.
• Utilizing cloud-based NLP services.
• Implementing real-time NLP pipelines.
• Best practices for integration.

Module 11: Model Monitoring and Maintenance

• Monitoring model performance and drift.
• Implementing model retraining and updating.
• Utilizing model monitoring tools and techniques.
• Handling model versioning and rollback.
• Best practices for model maintenance.

Module 12: Advanced NLP Techniques for Big Data

• Implementing question answering systems.
• Utilizing semantic search and information retrieval.
• Implementing text summarization and generation.
• Utilizing conversational AI and chatbots.
• Advanced techniques for large-scale NLP.

Module 13: NLP on Cloud Platforms

• Utilizing cloud-based NLP services.
• Deploying NLP models on AWS, Azure, and GCP.
• Optimizing cloud resources for NLP.
• Best practices for cloud-based NLP.

Module 14: NLP and Data Governance

• Implementing data governance policies in NLP.
• Utilizing metadata management tools.
• Implementing data lineage and data dictionary.
• Best practices for data governance.

Module 15: Future Trends in NLP for Big Data

• Emerging trends in NLP research and applications.
• Utilizing AI and automation in NLP workflows.
• Implementing explainable NLP models.
• Best practices for future NLP.

Training Approach

This course will be delivered by our skilled trainers who have vast knowledge and experience as expert professionals in the fields. The course is taught in English and through a mix of theory, practical activities, group discussion and case studies. Course manuals and additional training materials will be provided to the participants upon completion of the training.

Tailor-Made Course

This course can also be tailor-made to meet organization requirement. For further inquiries, please contact us on: Email: info@skillsforafrica.org, training@skillsforafrica.org  Tel: +254 702 249 449

Training Venue

The training will be held at our Skills for Africa Training Institute Training Centre. We also offer training for a group at requested location all over the world. The course fee covers the course tuition, training materials, two break refreshments, and buffet lunch.

Visa application, travel expenses, airport transfers, dinners, accommodation, insurance, and other personal expenses are catered by the participant

Certification

Participants will be issued with Skills for Africa Training Institute certificate upon completion of this course.

Airport Pickup and Accommodation

Airport pickup and accommodation is arranged upon request. For booking contact our Training Coordinator through Email: info@skillsforafrica.org, training@skillsforafrica.org  Tel: +254 702 249 449

Terms of Payment: Unless otherwise agreed between the two parties’ payment of the course fee should be done 7 working days before commencement of the training.