> For the complete documentation index, see [llms.txt](https://teamfar.gitbook.io/ktu-cse-resources/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://teamfar.gitbook.io/ktu-cse-resources/readme/semesters/s8.md).

# S8

{% content-ref url="/pages/lz59pyKpvHaH9RBW7LR5" %}
[Distributed Computing](/ktu-cse-resources/readme/semesters/s8/distributed-computing.md)
{% endcontent-ref %}

### 📚 Semester 8 Curriculum

1. **Distributed Computing** -Focuses on the principles and practices of distributed systems, covering topics such as distributed algorithms, synchronization, fault tolerance, and real-world applications.
2. **Program Elective III** (Choose one):
   * **Deep Learning**
     * Explores neural networks and deep learning architectures, emphasizing their applications in areas like image and speech recognition.
   * **Programming Paradigms**
     * Examines various programming paradigms, including functional, logical, and concurrent programming, highlighting their unique features and use cases.
   * **Network Security Protocols**
     * Delves into the design and analysis of protocols that ensure secure communication over networks.
   * **Soft Computing**
     * Introduces computational techniques that model complex real-world problems, including fuzzy logic, genetic algorithms, and neural networks.
   * **Embedded Systems**
     * Covers the design and development of embedded systems, focusing on hardware-software co-design and real-time constraints.
   * **Computer Vision**
     * Focuses on enabling computers to interpret and process visual information from the real world.
   * **Fuzzy Set Theory and Applications**
     * Introduces fuzzy set theory and its applications in handling uncertainty and imprecision in various domains.
3. **Program Elective IV** (Choose one):
   * **Mobile Computing**
     * Discusses principles and technologies of mobile computing, including mobile architectures, protocols, and application development.
   * **Parallel Computing**
     * Explores techniques and architectures for parallel processing to enhance computational speed and efficiency.
   * **Data Compression Techniques**
     * Covers methods for reducing the size of data for storage and transmission without significant loss of information.
   * **Data Mining**
     * Introduces techniques for discovering patterns and knowledge from large datasets.
   * **Client Server Architecture**
     * Focuses on the design and implementation of client-server systems and applications.
   * **Formal Methods and Tools**
     * Covers mathematically-based techniques for the specification, development, and verification of software and hardware systems.
4. **Project Phase II** -Continuation and completion of the capstone project initiated in Semester 7, emphasizing implementation, testing, and documentation.
5. **Comprehensive Viva** -An oral examination assessing the student's understanding and knowledge accumulated throughout the B.Tech program.


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