diff --git a/syllabus.md b/syllabus.md
index 9233173..9b603d2 100644
--- a/syllabus.md
+++ b/syllabus.md
@@ -16,26 +16,27 @@ covered.  Adversarial ML (what happens to ML algorithms in the
 presence of adversaries?)  will be also be discussed. List of some
 topics that we will cover (obviously not complete) are given below.
 
-Software Security
-  - Secure information flow
-  - Finding vulnerabilities
-  - Defensive measures and mitigations
-
 Differential Privacy
-  - Basic mechanisms
-  - Local Differential Privacy
+- Basic properties and examples
+- Advanced mechanisms
+- Local Differential Privacy
 
 Cryptographic Techniques
-  - Zero-knowledge proofs
-  - Secure multi-party computation
-  - Verifiable computation
+- Zero-knowledge proofs
+- Secure multi-party computation
+- Verifiable computation
+
+Language-based Security
+- Secure information flow
+- Differential privacy
+- Symbolic cryptography
 
 Adversarial Machine Learning
-  - Training-time attacks
-  - Test-time attacks
-  - Model theft attacks
+- Training-time attacks
+- Test-time attacks
+- Model-theft attacks
 
 Grading will be based on three components:
-  - Reading research papers and writing reviews
-  - Homeworks
-  - Class project
+- Reading research papers and writing reviews
+- Homeworks
+- Class project