Advanced Diploma in Computer Applications (ADCA)
*Course Overview*
The program focuses on advanced programming, software development, system design, and emerging technologies, preparing students for roles in software engineering, data analysis, cybersecurity, and IT management.
*Core Modules*
*1. Programming and Software Development*
- *Advanced Programming Concepts*
- Python, Java, C++ (OOP, multithreading, exception handling)
- Data structures: Trees, graphs, hash tables, heaps
- Algorithms: Dynamic programming, greedy algorithms, backtracking
- Complexity analysis (Big O notation)
- *Web Development*
- Frontend: HTML5, CSS3, JavaScript (ES6+), React/Angular
- Backend: Node.js, Django/Flask (Python), RESTful APIs
- Full-stack project integration (MERN/MEAN stack)
- *Mobile App Development*
- Android (Kotlin/Java) or iOS (Swift)
- Cross-platform frameworks: Flutter, React Native
*2. Database Management*
- *Advanced SQL*
- Query optimization, transactions, indexing
- PostgreSQL, MySQL, Oracle
- *NoSQL Databases*
- MongoDB, Cassandra, Firebase
- *Database Administration*
- Backup/recovery, security, normalization/denormalization
*3. Operating Systems & Networking*
- *OS Concepts*
- Process scheduling, memory management, virtualization
- Linux/Unix shell scripting
- *Computer Networks*
- OSI/TCP-IP models, routing protocols, subnetting
- Network security: Firewalls, VPNs, intrusion detection
*4. Software Engineering*
- *SDLC & Agile Practices*
- Waterfall, Scrum, Kanban, CI/CD pipelines
- *DevOps Tools*
- Docker, Kubernetes, Jenkins, Ansible
- *Version Control*
- Git, GitHub/GitLab workflows
*5. Cybersecurity*
- *Ethical Hacking*
- Penetration testing, vulnerability assessment (OWASP Top 10)
- Tools: Metasploit, Wireshark, Nmap
- *Cryptography*
- Symmetric/asymmetric encryption, digital signatures
*6. Cloud Computing*
- *Cloud Platforms*
- AWS/Azure/GCP: EC2, S3, Lambda, VPC
- Serverless architecture, microservices
- *Cloud Security & Cost Management*
*7. Data Science & Analytics*
- *Data Analysis*
- Python libraries: Pandas, NumPy, Matplotlib
- *Machine Learning Basics*
- Regression, classification, clustering (scikit-learn, TensorFlow)
- *Big Data Tools*
- Hadoop, Spark, Apache Kafka
*Elective Modules (Choose 2–3)*
1. *Artificial Intelligence & NLP*
- Neural networks, chatbots, sentiment analysis.
2. *IoT & Embedded Systems*
- Arduino/Raspberry Pi, sensor networks.
3. *Blockchain Technology*
- Smart contracts (Solidity), DApps, Ethereum.
4. *UI/UX Design*
- Figma, Adobe XD, usability testing.
*Practical Components*
- *Lab Work*
- Coding labs, network simulations (Cisco Packet Tracer), cybersecurity labs.
- *Projects*
- Real-world applications (e.g., e-commerce platforms, IoT systems).
- *Internship/Capstone Project*
- Industry collaboration or research-based project.
*Assessment Methods*
- Theory exams, coding tests, project presentations, and viva voce.
- Continuous evaluation via assignments, quizzes, and hackathons.
*Additional Components*
- *Workshops*
- Resume building, mock interviews, freelancing.
- *Certifications*
- AWS Certified Cloud Practitioner, Microsoft Azure Fundamentals, CEH.
- *Guest Lectures*
- Industry experts on AI, cybersecurity trends, and cloud innovations.
*Tools & Technologies Covered*
- *IDEs*: VS Code, IntelliJ, PyCharm
- *Collaboration*: Jira, Slack, Trello
- *Cloud*: AWS/Azure CLI, Docker Desktop