Natural Language Processing for Business Training Course

Module 1: Introduction to NLP in the Business Context

• Defining the scope of NLP: From basic search to generative intelligence
• Identifying high-value business use cases: Customer support, marketing, and legal
• The lifecycle of an NLP project: Data collection to model maintenance
• Overview of the modern NLP tech stack: Python, Spacy, NLTK, and Hugging Face
• Understanding the challenges of human language: Ambiguity, slang, and context
• Practical session: Setting up the development environment and exploring a real-world business text dataset

Module 2: Text Pre-processing and Linguistic Fundamentals

• Tokenization strategies: Breaking down sentences, words, and sub-words for analysis
• Cleaning raw data: Handling HTML tags, special characters, and stop-word removal
• Normalization techniques: Stemming vs. Lemmatization for reducing word variance
• Parts-of-Speech (POS) tagging and its importance in understanding sentence structure
• Dependency parsing to identify relationships between entities in business documents
• Practical session: Building a robust text-cleaning pipeline for messy customer review data

Module 3: Vectorization and Word Embeddings

• Converting text to numbers: The Bag-of-Words (BoW) model and its limitations
• Implementing TF-IDF (Term Frequency-Inverse Document Frequency) for keyword importance
• Introduction to Word2Vec and GloVe: Capturing semantic meaning in vector space
• Understanding the concept of "Contextual Embeddings" vs. static word vectors
• Visualizing high-dimensional text data using dimensionality reduction techniques
• Practical session: Creating a semantic search tool that finds documents based on meaning rather than just keywords

Module 4: Sentiment Analysis and Opinion Mining

• Rule-based vs. Machine Learning approaches to detecting emotional tone
• Building binary and multi-class sentiment classifiers (Positive, Neutral, Negative)
• Aspect-Based Sentiment Analysis (ABSA): Identifying sentiment toward specific product features
• Handling negation and intensifiers (e.g., "not good" vs. "very good") in text
• Integrating sentiment scores into business dashboards for real-time brand monitoring
• Practical session: Developing a sentiment analyzer to process and visualize Twitter/X feeds in real-time

Module 5: Automated Text Classification and Topic Modeling

• Supervised learning for text: Classifying emails, support tickets, and news articles
• Unsupervised learning: Discovering hidden themes using Latent Dirichlet Allocation (LDA)
• Feature selection and engineering for high-performance text classifiers
• Evaluating classification models: Precision, Recall, and the F1-Score in business metrics
• Clustering similar documents to organize large-scale corporate knowledge bases
• Practical session: Building an automated support ticket router that categorizes incoming queries by department

Module 6: Named Entity Recognition (NER) for Information Extraction

• Identifying and extracting business entities: Companies, people, locations, and dates
• Custom NER: Training models to recognize industry-specific terms like product IDs or legal clauses
• Relationship extraction: Understanding how entities interact within a sentence
• Transforming unstructured reports into structured databases for analysis
• Using regular expressions (Regex) to supplement machine learning extraction
• Practical session: Extracting key contract terms and expiration dates from a set of legal PDF documents

Module 7: Building Conversational AI and Chatbots

• The evolution of chatbots: From rigid decision trees to LLM-powered agents
• Designing conversation flows and intent recognition for customer service
• Integrating external APIs to allow bots to check order status or book appointments
• Managing dialogue state and context across multiple turns of conversation
• Best practices for bot-to-human handoff in enterprise environments
• Practical session: Designing and deploying a functional FAQ chatbot using a low-code/pro-code hybrid framework

Module 8: Text Summarization and Document Generation

• Extractive vs. Abstractive summarization: Choosing the right approach for business reports
• Using sequence-to-sequence models to condense long-form financial articles
• Automating the generation of routine business reports from structured data
• Evaluating summary quality: Understanding the ROUGE metric and human-in-the-loop validation
• Techniques for maintaining factual consistency in automated summaries
• Practical session: Implementing an automated "Executive Summary" generator for long-form market research papers

Module 9: Harnessing Large Language Models (LLMs) for Business

• Introduction to the Transformer architecture: The engine behind GPT and BERT
• Fine-tuning pre-trained models on specialized corporate data for higher accuracy
• Implementing Retrieval-Augmented Generation (RAG) to ground LLMs in private company data
• Advanced Prompt Engineering: Directing AI to produce high-quality professional content
• Managing costs and latency when scaling LLM applications in a business environment
• Practical session: Building a private knowledge base assistant that answers questions using only your company's internal documentation

Module 10: Deploying NLP Models and Ethical Governance

• Packaging NLP models as REST APIs for integration into web and mobile apps
• Monitoring model drift: When language shifts and models lose accuracy
• Addressing algorithmic bias and ensuring fairness in automated language processing
• Data privacy and security: Handling PII (Personally Identifiable Information) in text
• Creating a roadmap for AI governance and sustainable NLP adoption
• Practical session: Deploying a trained sentiment model to a cloud platform and testing its performance via API

Requirements:

Participants should be reasonably proficient in English.

Applicants must live up to Armstrong Global Institute admission criteria.

Terms and Conditions

1. Discounts: Organizations sponsoring Four Participants will have the 5th attend Free

2. What is catered for by the Course Fees: Fees cater for all requirements for the training – Learning materials, Lunches, Teas, Snacks and Certification. All participants will additionally cater for their travel and accommodation expenses, visa application, insurance, and other personal expenses.

3. Certificate Awarded: Participants are awarded Certificates of Participation at the end of the training.

4. The program content shown here is for guidance purposes only. Our continuous course improvement process may lead to changes in topics and course structure.

5. Approval of Course: Our Programs are NITA Approved. Participating organizations can therefore claim reimbursement on fees paid in accordance with NITA Rules.

Booking for Training

Simply send an email to the Training Officer on training@armstrongglobalinstitute.com and we will send you a registration form. We advise you to book early to avoid missing a seat to this training.

Or call us on +254720272325 / +254725012095 / +254724452588

Payment Options

We provide 3 payment options, choose one for your convenience, and kindly make payments at least 5 days before the Training start date to reserve your seat:

1. Groups of 5 People and Above – Cheque Payments to: Armstrong Global Training & Development Center Limited should be paid in advance, 5 days to the training.

2. Invoice: We can send a bill directly to you or your company.

3. Deposit directly into Bank Account (Account details provided upon request)

Cancellation Policy

1. Payment for all courses includes a registration fee, which is non-refundable, and equals 15% of the total sum of the course fee.

2. Participants may cancel attendance 14 days or more prior to the training commencement date.

3. No refunds will be made 14 days or less before the training commencement date. However, participants who are unable to attend may opt to attend a similar training course at a later date or send a substitute participant provided the participation criteria have been met.

Tailor Made Courses

This training course can also be customized for your institution upon request for a minimum of 5 participants. You can have it conducted at our Training Centre or at a convenient location. For further inquiries, please contact us on Tel: +254720272325 / +254725012095 / +254724452588 or Email training@armstrongglobalinstitute.com

Accommodation and Airport Transfer

Accommodation and Airport Transfer is arranged upon request and at extra cost. For reservations contact the Training Officer on Email: training@armstrongglobalinstitute.com or on Tel: +254720272325 / +254725012095 / +254724452588