Echelon Institute of Technology (Faridabad, Delhi NCR) offers a future-ready B.Tech in Computer Science & Engineering with specialization in Artificial Intelligence & Machine Learning, blending strong CS foundations with applied AI/ML, deep learning, NLP, and computer vision, supported by modern labs and industry-oriented pedagogy.

• Program credibility: Public program listings and directories profile Echelon’s B.Tech CSE (AI & ML) as a full-time 4-year program with a dedicated intake and transparent fee information.

• Hands-on approach: Practical labs, tools, and project work across semesters in AI, ML, DL, CV, and NLP to make graduates industry-ready from day one.

Program Highlights: B.Tech CSE (AI & ML)

• Duration & intake: 4 years, with a dedicated AI & ML specialization intake, following semester-wise structure and labs per GGSIPU scheme.

• Curriculum coverage: Core CS (DSA, OS, DBMS), AI foundations, ML algorithms, deep learning, NLP, computer vision, reinforcement learning, plus capstone projects and internship pipeline.

• Tools & platforms: Python, TensorFlow, Keras, PyTorch, scikit‑learn, OpenCV, Jupyter; exposure to MATLAB and big-data/analytics stacks where relevant.

• Labs & infrastructure: Structured lab calendar (Data Structures, DBMS, OS, AI/ML/DL/CV labs), modern computing environments, and departmental facilities for AIML & Data Science.

• Career pathways: AI/ML Engineer, Data Scientist, NLP Engineer, Computer Vision Engineer, Research roles, and product/data engineering positions across BFSI, e‑commerce, healthtech, manufacturing, and SaaS.

What You’ll Learn

• AI/ML core: Supervised/unsupervised learning, neural networks, deep learning, model evaluation, MLOps basics, and ethical AI considerations aligned to common AI/ML curricula in India.

• Domain applications: Recommender systems, fraud detection, predictive analytics, conversational AI, vision models, and smart automation projects mirroring industry demand. 

• Project portfolio: Chatbots, image/speech recognition, recommendation engines, analytics projects, with structured semester-wise lab experiments and major project in final year.

Admissions & Eligibility

• Entrance & criteria: Typical eligibility is 10+2 with PCM; JEE Main/CUET/IPU routes commonly apply within the GGSIPU ecosystem; prospective students should follow the current counseling/admission notifications each cycle. 

• Seats & fees: Public sources list the AI & ML specialization with a defined seat matrix and a transparent total fee band, with hostel fees published separately for planning.

• Important note: Always verify live intake, fees, reservations, and timelines on official advisories before applying.

• Placements & Industry Exposure

  • Placement readiness: Emphasis on practical projects, internships, hackathons, and interview preparation aligned to AI/ML roles and broader software engineering tracks.

  • Recruiter relevance: AI/ML, data, and software roles with tech services, product companies, and startups remain strong across Delhi NCR; directories indicate robust placement orientation for Echelon’s CS specializations.

  • Portfolio-first approach: Students graduate with GitHub-backed code, model notebooks, and capstone outcomes mapped to real problem statements, boosting shortlisting rates in AI/ML pipelines.