NT Academy's program is an intensive, job-oriented program designed for individuals looking to build practical skillsets. We combine structured online/offline classes, direct mentor interaction, weekly doubt resolution sessions, and actual industry project tasks to help you bridge the gap between learning and real job execution.
Program Overview
What You Will Master:
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Hands-on experience with actual industry-standard tools
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6+ real-world projects and a comprehensive Capstone
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Live Interactive doubt-clearing sessions with tech experts
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1-on-1 resume reviews, mock interviews, and portfolio curation
LMS Course Curriculum
Step-by-step syllabus structured across academic weeks. Click on each module banner to view detailed lectures, resources, labs, and exams details.
- 1.1 Python syntax, control structures & list comprehensions (Video)
- 1.2 Object-Oriented Programming (OOP) in Python data tools (Lab)
- 1.3 Data structures: Lists, Dictionaries, Sets & Tuples (Document)
- 1.4 Exception Handling, modules import & Pip environments (Quiz)
- 2.1 NumPy Arrays: Matrix multiplications, indexing & slicing (Video)
- 2.2 pandas DataFrames: Loading datasets, filtering & sorting (Lab)
- 2.3 Data Cleaning: Handling missing values, duplicates & datatypes (Video)
- 2.4 Merging, joining & concatenating multi-source datasets (Quiz)
- 3.1 Descriptive Statistics: Mean, Median, Mode, Variance & SD (Video)
- 3.2 Probability distributions, CLT & Hypotheses testing (Lab)
- 3.3 A/B testing statistical checks: p-values & Z-tests (Document)
- 3.4 Correlation vs. Causation, ANOVA tests configurations (Quiz)
- 4.1 Custom plotting with Matplotlib: lines, bars & scatters (Video)
- 4.2 Advanced statistical charts using Seaborn: box, violin & heatmaps (Lab)
- 4.3 Styling charts, layouts alignment & axis configurations (Document)
- 4.4 Interactive dashboards with Plotly & Streamlit app layouts (Quiz)
- 5.1 Supervised Learning: Linear & Logistic Regressions (Video)
- 5.2 Decision Trees, Random Forests & Ensemble algorithms (Lab)
- 5.3 Unsupervised Learning: K-Means clustering & PCA dimensions (Video)
- 5.4 ML Model Evaluations: Accuracy, Precision, Recall, ROC-AUC (Quiz)
- 6.1 Neural Networks basics, weights & backpropagation (Video)
- 6.2 Large Language Models (LLM) APIs: OpenAI prompt structures (Lab)
- 6.3 Containerizing models using Docker & Streamlit wrappers (Document)
- 6.4 Final Capstone Defense: Code walkthroughs & model verification (Exam)
Key Program Perks
Certified Credentials
Get a verifiable blockchain registry certificate listing key skills and project verification.
Direct Referrals
Get priority referrals across our partner network of startups and mid-market tech firms.
Lifetime Resources
Get lifetime updates to recorded class videos, code bases, and slack channels.
Frequently Asked Questions
Any student, college graduate, or working professional interested in tech, design, or marketing can enroll. No prior coding or design background is required as we teach all tracks from the complete ground up.
Yes, absolutely! We support flexible hybrid structures. You can request a batch transition from online virtual classrooms to our offline learning campus in Noida anytime during the program duration.
We provide comprehensive placement support including 1-on-1 mock interviews, professional resume structuring, LinkedIn branding workshops, active hiring drive listing, and direct referrals to hiring partners.
Yes, we offer a full refund if requested at least 3 days before the official batch launch date. No refunds are processed after the batch sessions have officially started.