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3rd Floor, Sahay Complex, Near IIM Tiraha, Lucknow | Admissions Open 2026–27
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Industrial Training

Artificial Intelligence & Machine Learning Course in Lucknow & Online

Learn Intelligence. Build Real Solutions..

Course at a glance
Artificial Intelligence & Machine Learning at BPST Academy, Lucknow is a 45 days or 3 months · 6 months beginner-friendly course covering Python for AI, Maths for ML, Supervised Learning, Unsupervised Learning. It suits engineering and computer science students aiming for roles in applied AI, machine learning engineering, and algorithmic problem solving. Classes run in the Lucknow classroom and live online. Until Diwali (8 Nov 2026) you can pre-book a seat for ₹49, adjusted in the course fee.
Duration
45 Days · 3 Months · 6 Months
Level
Beginner friendly
Mode
Classroom · Online
Pre-book
₹49 till Diwali
Diwali gift
₹49

Reserve your seat in the next Artificial Intelligence & Machine Learning batch. Adjusted in your course fee.

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What Is the Artificial Intelligence & Machine Learning Course?

Build intelligent solutions with machine learning algorithms, predictive systems, and real-world AI applications from math foundations to production models.

Who is it for?

Engineering and computer science students aiming for roles in applied AI, machine learning engineering, and algorithmic problem solving.

Prerequisites

Basic math and logical reasoning. Python basics covered from day one.

What Does the Artificial Intelligence & Machine Learning Course Cover?

  • Python for AI / ML: Vectorized computing, matrix operations, statistical libraries
  • Machine Learning Basics: Supervised vs unsupervised learning, data splitting, validation
  • Core Algorithms: Linear/Logistic Regression, Decision Trees, Random Forests, SVM, K-Means
  • Model Training & Evaluation: Cross-validation, precision, recall, F1-score, ROC curves
  • Feature Engineering: Handling categorical data, scaling, dimensionality reduction
  • Deep Learning Concepts: Artificial Neural Networks, activation functions, backpropagation
  • AI API Integration: Consuming pre-trained models and deploying inference APIs

Artificial Intelligence & Machine Learning Syllabus — Module by Module

Module 01
Python for AI
  • NumPy, Pandas
  • Data visualization
  • Jupyter notebooks
  • Clean code
Module 02
Maths for ML
  • Linear algebra essentials
  • Statistics & probability
  • Calculus intuition
  • Gradient descent
Module 03
Supervised Learning
  • Linear & logistic regression
  • Decision trees, random forest
  • SVM, KNN
  • Model evaluation
Module 04
Unsupervised Learning
  • K-means clustering
  • Hierarchical clustering
  • PCA
  • Anomaly detection
Module 05
Deep Learning Intro
  • Neural networks
  • TensorFlow / Keras basics
  • CNN for images
  • NLP basics
Module 06
Deployment
  • Feature engineering
  • Model tuning
  • FastAPI / Flask serving
  • Deploy model to cloud

What Will You Learn Week by Week?

Choose the format that fits your semester or career plan. Each roadmap ends with a deployed project.

Core ML algorithms & evaluation Daily algorithm coding & evaluation
Week 1
Python + ML Basics
NumPy, Pandas, introduction to machine learning paradigms
Week 2
Data Preprocessing
Feature scaling, encoding, missing values, train/test split
Week 3
Beginner Models
Regression, Classification, Decision Trees with Scikit-learn
Week 4
Evaluation & Tuning
Confusion matrix, hyperparameter tuning, model score comparison
Final Phase
Mini AI Use Case
Train and test a working predictive model on real data
Applied ML & deep learning intro Algorithm labs & real-world datasets
Weeks 1–2
Python & ML Concepts
Mathematical intuitions, vectorized math, data pipelines
Weeks 3–4
Model Building
Ensemble methods, Random Forest, XGBoost, clustering
Weeks 5–6
Evaluation & Tuning
Cross-validation, bias-variance tradeoff, optimization
Weeks 7–8
Deep Learning Intro
Perceptrons, multi-layer neural networks, backprop basics
Weeks 9–12
Guided Project
End-to-end predictive pipeline with FastAPI inference endpoint
Deep learning, vision & deployment Model deployment, pipelines & interview readiness
Weeks 1–4
AI / ML Foundations
Linear algebra, probability, data ingestion, baseline modeling
Weeks 5–8
Data Preparation & Feature Store
Advanced feature engineering, automated preprocessing pipelines
Weeks 9–12
ML Modeling Rigor
Advanced regression, classification, clustering, anomaly detection
Weeks 13–16
Multiple Algorithms & Ensembles
Stacking, boosting, model explainability (SHAP/LIME)
Weeks 17–20
Deep Learning & Vision Intro
Convolutional neural nets, image recognition, transfer learning
Weeks 21–24
End-to-End Project & Career Prep
Model serialization, Docker deployment, resume, technical mock interviews

Projects, Outcomes & Tools

Projects you build

  • House price predictor
  • Customer segmentation
  • Image classifier web app
  • Credit Risk & Loan Default Classifier
  • Automated Defect Detection in Manufacturing

You will be able to

  • Build and evaluate ML models
  • Choose the right algorithm for a problem
  • Serve a model through an API
  • Explain ML concepts in interviews

Tools & tech

PythonScikit-learnNumPyPandasTensorFlowKerasFastAPI

BitProSoftTech training certificate; 6-month program includes an internship letter

Credit Risk & Loan Default ClassifierSimulated Industry Sprint

Preprocessing banking metrics, handling class imbalance, and training predictive classifiers.

PythonScikit-LearnFastAPI
Automated Defect Detection in ManufacturingGuided Portfolio Project

Image classification pipeline identifying assembly line defects.

PyTorchOpenCVPython

How Is Artificial Intelligence & Machine Learning Taught at BPST Academy?

Every batch follows our simulated software-company model: fundamentals first, daily hands-on coding, team formation with real roles, Agile sprints with daily stand-ups, code reviews, testing and live deployment — guided by working IT professionals who act as your project managers.

Daily hands-on practice

Write and debug code in every session, not just watch slides.

Mentor as project manager

Sprints, pull-request reviews and deadlines like a real team.

Live, demo-able projects

Your work goes on GitHub and a live URL recruiters can open.

Artificial Intelligence & Machine Learning — Frequently Asked Questions

Artificial Intelligence & Machine Learning runs for 45 Days · 3 Months · 6 Months. You can study in the Lucknow classroom (3rd Floor, Sahay Complex, Near IIM Tiraha) or join the same batch live online from anywhere in India.

Engineering and computer science students aiming for roles in applied AI, machine learning engineering, and algorithmic problem solving. Prerequisite: Basic math and logical reasoning. Python basics covered from day one.

The course fee depends on the duration and mode you choose and is shared with you on WhatsApp right after pre-booking. As a Diwali gift, you can reserve your seat for just ₹49 until 8 November 2026 (23:59 IST). The ₹49 is adjusted in your course fee.

Yes. BitProSoftTech training certificate; 6-month program includes an internship letter. You also leave with project work you can show to employers.

Yes — we provide job assistance: resume and LinkedIn/Naukri profile reviews, mock technical and HR interviews, and relevant interview opportunities. We do not make placement-guarantee claims; we make sure your skills and portfolio are genuinely job-ready.

Last updated 2026-09-25

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