Data Science with AI – Advanced Certification
Master end-to-end data science, ML, AI frameworks, and deployment workflows with expert mentorship, portfolio projects, and interview preparation.
Duration
7 Months
Fees
₹1,20,000
Mode
Online & Offline
Special batch for working professionals
Placement
100% Job Placement
Guarantee Assurance
Course Overview
The Data Science with AI – Advanced Certification compresses 12+ months of industry learning into a high-intensity 7‑month journey. Learners advance from statistics and Python fundamentals to production-grade ML ops workflows while consistently building portfolio-grade solutions.
Weekly mentor guidance, resume reviews, and interview simulations ensure you graduate with employer-ready deliverables plus the confidence to present them.
Why This Course?
- End-to-end AI & Data Science mastery using real frameworks
- Hands-on projects spanning notebooks, APIs, and dashboards
- Expert guidance with resume, GitHub grooming, and mock interviews
- Dedicated placement cell focused on high-paying data careers
Career Outcomes
- Data Scientist
- Machine Learning Engineer
- AI Specialist / NLP Engineer
- Business Intelligence Analyst
- Product Data Consultant
Course Curriculum
Learn-by-doing modules that turn brochure promises into portfolio results
Python, Statistics & Data Engineering (Month 1)
- Python foundations, object-oriented design, scripting best practices
- Exploratory data analysis with pandas, NumPy, Matplotlib, Seaborn
- Statistics for analytics: probability, hypothesis testing, experiment design
- SQL + NoSQL pipelines to land curated datasets in analytics-ready layers
Project: Automated KPI data mart (Python + SQL) with quality checks.
Machine Learning Foundations (Months 2-3)
- Feature engineering, scaling, encoding, class imbalance resolution
- Supervised learning: regression, tree ensembles, gradient boosting
- Unsupervised learning: clustering, PCA/UMAP, anomaly detection
- Model evaluation dashboards with cross-validation and SHAP insights
Project: Customer lifecycle prediction with explainable ML playbook.
Deep Learning & Applied AI (Months 4-5)
- Neural network basics, CNNs for vision, RNN/LSTM/Transformers for sequences
- Transfer learning, prompt engineering, and retrieval-augmented generation (RAG)
- LLM fine-tuning, embeddings search, and conversational AI design
- Responsible AI: fairness audits, monitoring, human-in-loop controls
Project: Multi-modal AI assistant (text + image) with FastAPI endpoint.
MLOps & Career Sprint (Months 6-7)
- Model packaging with Docker, CI/CD pipelines, and cloud deployment (AWS/GCP)
- Scheduling with Airflow, experiment tracking via MLflow, data versioning
- Job simulations: whiteboard rounds, case study storytelling
- Portfolio polish: GitHub curation, LinkedIn branding, resume narratives
Project: Production-ready ML workflow with monitoring & rollback strategy.
Additional Benefits
Regular live classes (2 hrs daily) with doubt-clearing support
Personalised training plans with 1:1 mentorship
Weekend personality development & communication labs
20+ real projects and domain case studies
20+ industry-level mock interviews and feedback loops
Interview preparation, resume workshops, and ATS-friendly templates
Portfolio management with LinkedIn optimisation & GitHub reviews
Mental health & confidence coaching to stay job-ready
Internship certification plus globally recognised course credential
Small interactive batches for peer learning and accountability
Note for Learners
Graduates exit with portfolio artefacts that reflect 1+ year of hands-on experience, making lateral moves or fresh entries into AI teams realistic within 7 months.