Course Overview

This course offers a comprehensive dive into the intersection of data science and cybersecurity, emphasizing how advanced analytical techniques can be applied to detect, understand, and counter cyber threats. From identifying malicious activities to predicting potential vulnerabilities, you will explore how data can become a powerful weapon in the fight against cybercrime. 

You will gain hands-on experience in building solutions using supervised and unsupervised machine learning, neural networks, and natural language processing (NLP). The course focuses on real-world challenges such as malware detection, intrusion prevention, and phishing mitigation, reinforced through practical examples, case studies, and industry-proven strategies. 

By the end of this course, learners will be equipped with the technical know-how and strategic mindset to develop and deploy data-driven security solutions. You'll be prepared to anticipate and respond to complex cyber threats using cutting-edge data science techniques, positioning yourself as a valuable asset in the rapidly evolving cybersecurity landscape. 

What You Will Learn

  • Understand the cybersecurity threat landscape and how data science can enhance detection and defense.
  • Collect , preprocess , and analyze cybersecurity data for meaningful insights and model readiness.
  • Apply supervised and unsupervised machine learning techniques to detect threats and anomalies.
  • Leverage neural networks and natural language processing (NLP) to analyze and identify malicious patterns in text-based data.
  • Evaluate model performance , apply optimization techniques , and ensure ethical and regulatory compliance in real-world cybersecurity applications.

Program Curriculum

  • Overview of Data Science
  • Introduction to Cybersecurity
  • Data Sources in Cybersecurity
  • Exploratory Data Analysis and Pre-processing
  • Chapter 1 Quiz

  • Regression Algorithms
  • Classification Algorithms
  • Chapter 2 Quiz

  • Logistic Regression
  • Support Vector Machines
  • Chapter 3 Quiz

  • Isolation Forest
  • Detecting Insider Threat Using Isolation Forest
  • Chapter 4 Quiz

  • Introduction to Neural Networks
  • Detecting Threat Intelligence from Text Using NLP and LSTM
  • Chapter 5 Quiz

  • Real-world Applications
  • Ethical Angles
  • Regulatory Aspects
  • Chapter 6 Quiz
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Instructor

Manas Dasgupta

Manas holds an MSc in AI-ML from Liverpool John Moores University (LJMU), UK. His expertise includes Generative AI (RAG application development using frameworks like LangChain and LlamaIndex), Machine Learning, Data Science, and Predictive Analytics, with a focus on techniques such as Supervised and Unsupervised Learning, Deep Neural Networks, and Clustering.

His research focuses on Natural Language Processing (NLP) using Deep Learning methods like Siamese Networks, Encoder-Decoder techniques, and Language Embeddings (e.g., BERT).

With over 20 years of experience in IT, primarily in Financial Services, Manas has developed solutions for top banks and institutions, including Natwest, ANZ, KBC, Visa, and Experian.

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