Online MCA in Natural Language Processing Course

Sentiment Analysis | Speech Processing | Language Modelling | Chatbots & Virtual Assistants

Duration

2 Years

(4 Semesters)

1st Semester Fees

INR 32,875/-

2nd–4th Semester Fees

INR 32,375/-

per sem

Total Fees

INR 1,30,000/-

About Natural Language Processing

The elective explains how computers understand human language using text classification, sentiment analysis, speech processing, and language modelling. It also highlights applications like chatbots and virtual assistants.

Learning Modules

Learn how computers categorize and classify text into predefined categories, enabling automated organization and understanding of textual data.

Analyze text to detect emotions, opinions, or sentiment polarity, helping machines understand customer feedback, reviews, and social media posts.

Process and interpret spoken language, enabling applications like speech recognition, voice commands, and real-time transcription.

Learn how machines predict and generate human language sequences, forming the foundation for NLP applications like translation and text generation.

Build intelligent conversational agents that understand and respond to user queries, providing automated support and assistance.

Career Path

Designs and builds both front-end and back-end components of web applications. Works with modern frameworks, APIs, cloud deployment, and scalable architectures.

Develops Android and iOS applications using native or cross-platform frameworks. Focuses on performance, UI/UX, and integration with cloud-based backends.

Automates development pipelines, manages CI/CD, and ensures smooth deployment. Works with containerization, monitoring tools, and cloud infrastructure.

Evaluates business requirements and designs technology solutions. Works closely with stakeholders to analyze workflows and recommend system improvements.

Builds machine learning models and integrates AI solutions into applications. Uses modern ML frameworks, data pipelines, and responsible-AI practices.

Leads IT projects, manages timelines, and coordinates cross-functional teams. Ensures successful delivery of technology solutions aligned with business goals.

Designs, develops, tests, and maintains software applications. Works with modern languages, design patterns, and agile development practices.

Analyzes large datasets to uncover insights and build predictive models. Uses statistical methods, machine learning, and data visualization tools.

Builds and deploys applications on cloud platforms like AWS, Azure, or GCP. Works with serverless computing, cloud-native tools, and scalable architectures.

Protects systems, data, and networks from cyber threats. Performs risk assessments, monitors attacks, and implements security controls.