Sentiment Analysis with AI and NLP teaches investors how to transform social media, news, and online discussions into measurable insights that drive smarter financial decisions. Through practical NLP methods and machine learning models, learners discover how market psychology shapes price action and how to build sentiment-driven trading signals. The course includes real-time dashboards, case studies, and strategy development across retail and institutional contexts. Participants finish equipped to extract sentiment, detect manipulation, and apply AI ethically in modern investing.
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Skills & learning objectives
There are 10 modules in this class
- What is Sentiment Analysis?Unlock this class to watch3m 17s
- Role of Sentiment in Investor Psychology and Market BehaviorUnlock this class to watch2m 56s
- Historical Evolution: From Analyst Opinions to NLP ModelsUnlock this class to watch3m 34s
- Sentiment in Retail Trading vs. Institutional TradingUnlock this class to watch3m
- Structured vs. Unstructured DataUnlock this class to watch1m 30s
- Key Platforms: Reddit, Twitter, StockTwits, YouTube, DiscordUnlock this class to watch1m 36s
- Collecting Data Using APIs and Web ScrapingUnlock this class to watch1m 34s
- Preprocessing Text: Tokenization, Cleaning, LemmatizationUnlock this class to watch1m 19s
- From Text to Signal: Creating Sentiment ScoresUnlock this class to watch1m 33s
- Introduction to NLP in FinanceUnlock this class to watch1m 20s
- Lexicon-Based Models: VADER, FinBERT, TextBlobUnlock this class to watch1m 52s
- Supervised ML Models: Logistic Regression, SVMUnlock this class to watch1m 34s
- Deep Learning & Transformers: BERT, GPT, LLMs in FinanceUnlock this class to watch1m 57s
- Common Pitfalls: Overfitting, Noise, and False PositivesUnlock this class to watch1m 53s
- Overlaying Sentiment on Technical/Quant ModelsUnlock this class to watch1m 31s
- Portfolio Allocation Based on Sentiment TrendsUnlock this class to watch2m 56s
- Cross-Asset Sentiment Mapping (Crypto, Equities, Forex)Unlock this class to watch1m 19s
- Real-Time Sentiment Dashboards: Design and VisualizationUnlock this class to watch1m 13s
- Gamification and Emotion-Driven Alerts for Retail UsersUnlock this class to watch56s
- overview of Leading PlatformsUnlock this class to watch1m 55s
- Comparing APIs: Pricing, Latency, Coverage, ReliabilityUnlock this class to watch1m 42s
- DIY vs. Commercial Sentiment FeedsUnlock this class to watch1m 35s
- Integrating APIs into Python and ExcelUnlock this class to watch1m 25s
- Vendor Evaluation Checklist for Retail InvestorsUnlock this class to watch1m 42s
- Tesla, AMC & GameStop: Retail Sentiment WavesUnlock this class to watch1m 49s
- backtesting a Reddit Sentiment-Based StrategyUnlock this class to watch1m 23s
- Crypto Token Hype Cycles and Social Media TriggersUnlock this class to watch1m 30s
- Influence of Influencers: YouTube, TikTok, and MicrobloggingUnlock this class to watch1m 15s
- Sentiment + Momentum Hybrid StrategiesUnlock this class to watch1m 11s
- Ethical AI Use in Retail InvestingUnlock this class to watch1m 11s
- Misinformation Economics: Fake News, Bots, and DeepfakesUnlock this class to watch52s
- Detecting and Preventing Synthetic Sentiment SignalsUnlock this class to watch54s
- Transparency in AI-Driven RecommendationsUnlock this class to watch49s
- Regulatory Outlook: SEC, EU AI Act, and Future OversightUnlock this class to watch1m 10s
- Cognitive Biases Amplified by Sentiment DataUnlock this class to watch1m 9s
- Anchoring and Confirmation in Social TradingUnlock this class to watch1m 6s
- Framing Effects in App Notifications and DashboardsUnlock this class to watch54s
- Building Trust in Sentiment-Driven ToolsUnlock this class to watch52s
- Client Communication in Advisory PlatformsUnlock this class to watch55s
- From Research to Action: Deploying Sentiment StrategiesUnlock this class to watch1m 39s
- Paper Trading and Live Testing with TradingView and QuantConnectUnlock this class to watch1m 35s
- Risk Management in Sentiment-Driven SystemsUnlock this class to watch1m 27s
- Integrating Sentiment Models into Robo-AdvisorsUnlock this class to watch1m 27s
- Low-Code and No-Code Solutions for Retail DeploymentUnlock this class to watch1m 22s
- ClosingUnlock this class to watch55s
This class is part of the following certifications
Certified Portfolio & Fund Manager (CPFM)
63 ClassesUnlimited interactive exercises
Unlock Certificate
Certificate in AI-Powered Financial Analysis (CAFA)
56 ClassesUnlimited interactive exercises
Unlock Certificate
ClassFAQs
The course aims to teach learners how to transform unstructured text data into measurable sentiment signals for financial markets and business intelligence using NLP, machine learning, and deep learning models.
The course is designed for analysts, traders, data scientists, and professionals seeking to apply sentiment analysis in trading, investment research, brand monitoring, and enterprise decision-making.
The module covers text cleaning, tokenization, stemming, lemmatization, stop-word removal, vectorisation, and embeddings such as Word2Vec and GloVe.
The course explains lexicon-based methods, TF-IDF features, Naïve Bayes, logistic regression, SVMs, RNNs, LSTMs, transformer models such as BERT, and fine-tuning techniques for sentiment classification.
Learners will gain the ability to evaluate models using metrics like precision, recall, F1, and ROC-AUC, detect bias, apply ethical guidelines, build dashboards, and deploy sentiment pipelines using APIs and visualization tools.
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