SP IT Academy / AI / ML
AI / MACHINE LEARNING

Become a Job-Ready AI & ML Engineer.

Learn machine learning, deep learning, neural networks and applied AI with Python through practical training, real projects and placement-focused preparation.

Start Your Journey → Explore Curriculum
100% Practical Learning
6–8 Months Program
6+ Major Projects
train.py

import tensorflow as tf

model = tf.keras.Sequential([

layers.Dense(128, activation="relu"),

layers.Dense(10, activation="softmax"),

])

model.fit(x_train, y_train, epochs=10)

🧠 ML
TF TensorFlow
🐍 Python
01 Duration

6–8 Months

02 Mode

Classroom + Practical

03 Projects

6+ Real Projects

04 Career

Placement Preparation

COURSE DNA

Everything you need to build applied AI systems.

One structured path from Python and machine learning to deep learning and deployment.

Python

Build strong programming fundamentals for AI work.

MTH

Math for ML

Linear algebra, calculus and probability essentials.

ML

Machine Learning

Build and evaluate classical ML models.

DL

Deep Learning

Train neural networks with modern frameworks.

NN

Neural Networks

Understand how networks learn end to end.

NLP

NLP Basics

Work with text data and language models.

CV

Computer Vision

Build image classification models with CNNs.

DEP

Model Deployment

Serve trained models behind a simple API.

LEARNING JOURNEY

From your first model to applied AI projects.

Learn in the order the industry actually needs you to learn.

01
FOUNDATION

Python Foundations

Build the Python skills needed for AI and ML work.

Core Python NumPy Pandas Environments
02
MATH

Math for ML

Understand the maths that powers machine learning.

Linear Algebra Calculus Basics Probability Gradients Optimisation
03
ML

Classical Machine Learning

Build supervised and unsupervised models and evaluate them.

Regression Classification Clustering Ensembles Evaluation
04
DEEP LEARNING

Deep Learning Foundations

Train neural networks with TensorFlow / Keras.

Perceptron Activation Functions Backprop Loss Functions Regularisation
05
PRACTICE

Neural Networks in Practice

Design, train and debug real networks.

Keras Layers Callbacks Overfitting Transfer Learning
06
APPLIED

Applied AI: NLP & Vision

Apply deep learning to text and images.

Text Preprocessing Embeddings CNNs Image Classification Pretrained Models
07
CAREER

Capstone & Interview Preparation

Prepare for AI / ML interviews and project discussions.

ML Concepts DL Concepts Case Studies Resume Mock Interviews
COMPLETE CURRICULUM

What you will actually learn.

MODULE 01 01

Python for AI

Build the programming base for everything that follows.

  • Variables & Types
  • Control Flow
  • Functions
  • OOP Basics
  • NumPy
  • Virtual Envs
MODULE 02 02

Math Essentials

Learn just enough maths, applied to ML.

  • Vectors & Matrices
  • Matrix Operations
  • Derivatives
  • Gradients
  • Probability
  • Distributions
MODULE 03 03

Data Handling & EDA

Prepare data for modelling.

  • Pandas
  • Cleaning
  • Feature Engineering
  • Scaling
  • Train / Test Split
  • Visualization
MODULE 04 04

Supervised & Unsupervised ML

Build the core family of ML models.

  • Linear & Logistic Regression
  • Decision Trees
  • Random Forest
  • SVM
  • K-Means
  • PCA
MODULE 05 05

Model Evaluation

Make models reliable and honest.

  • Metrics
  • Confusion Matrix
  • Cross Validation
  • Bias / Variance
  • Hyperparameter Tuning
  • Data Leakage
MODULE 06 06

Deep Learning Foundations

Understand how neural networks learn.

  • Neurons & Layers
  • Activation Functions
  • Forward Pass
  • Backpropagation
  • Optimisers
  • Loss Functions
MODULE 07 07

CNNs & Computer Vision

Build models that understand images.

  • Convolutions
  • Pooling
  • CNN Architectures
  • Data Augmentation
  • Transfer Learning
  • Image Classification
MODULE 08 08

NLP Fundamentals

Build models that work with language.

  • Text Cleaning
  • Tokenisation
  • Bag of Words / TF-IDF
  • Word Embeddings
  • RNN Basics
  • Sentiment Analysis
MODULE 09 09

MLOps & Deployment Basics

Get a model out of the notebook.

  • Saving Models
  • REST API with Flask
  • Inference
  • Versioning
  • Monitoring Basics
  • Reproducibility
MODULE 10 10

Capstone & Placement

Deliver an applied AI project and prepare for interviews.

  • End-to-End Project
  • Presentation
  • ML / DL Interview Questions
  • Resume
  • Portfolio
  • Mock Interviews
PROJECT BASED LEARNING

Don't just learn. Build.

Your portfolio should prove what you can build, not just what you have studied.

01
MACHINE LEARNING

Prediction Model

Build and evaluate a classical ML model on a real tabular dataset.

scikit-learn Evaluation Tuning
02
COMPUTER VISION

Image Classifier

Train a CNN to classify images and improve it with transfer learning.

Keras CNN Transfer Learning
03
NLP

Sentiment Analysis App

Build a text-classification model and expose it through a simple interface.

NLP Embeddings Flask
04
CAPSTONE PROJECT

Applied AI Project

Take a real problem from data and modelling through deep learning, evaluation and a deployed prediction API.

Python TensorFlow Evaluation Flask API GitHub
CAREER PREPARATION

Learn the skills. Prepare to get hired.

Technical skills are only one part of becoming job-ready. We prepare you for the complete hiring process.

✓ Resume Building

Create an AI / ML-focused resume.

✓ Project Portfolio

Showcase model notebooks and applied projects.

✓ Technical Interviews

ML, deep learning, Python and maths questions.

✓ Case Study Practice

Practice framing open-ended AI problems.

✓ Mock Interviews

Experience real interview-style sessions.

YOUR CAREER JOURNEY 01 → 05
01 Learn
02 Practice
03 Build Projects
04 Build Portfolio
05 Apply for Jobs
CERTIFICATION

Finish the journey with a portfolio you can show.

Receive your SP IT Academy AI / Machine Learning certificate after successfully completing the required curriculum and projects.

01 Course Completion Certificate
02 Project-Based Assessment
03 Portfolio Projects
SP IT ACADEMY
PROFESSIONAL CERTIFICATE

This is to certify that

Student Name

has successfully completed the

AI / Machine Learning
SP IT Academy Certificate ID: SPAIML-2026
ADMISSION

Ready to start your AI / ML journey?

Talk to our counsellor and understand the batch, curriculum, fees and career path.

01

Enquire

Share your basic details with us.

02

Counselling

Discuss your goals with our counsellor.

03

Choose Your Batch

Select the schedule that works for you.

04

Start Learning

Begin your AI / ML journey.

Get Course Details

Our team will contact you shortly.

SP IT ACADEMY

Your AI / ML career starts with one decision.

Learn. Build. Practice. Get ready for the industry.

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