Learn. Practise. Apply.

Artificial Intelligence
Course at LearnAI

Explore artificial intelligence through a 22-module curriculum and 5 project topics. Develop analytics and programming foundations, then explore machine learning, deep learning, computer vision, time series, natural language processing and chatbots. The curriculum connects Power BI, SQL, Python and data preparation with AI model building and practical project topics.

Online India & worldwideClassroom Learn at a branchHybrid Online + classroom

Classroom: Dilsukhnagar, Hyderabad

Online: USA, Canada, UK, Australia, New Zealand and Germany

Ask about your preferred mode, branch and upcoming batch.

Ask About This Course ↗View Curriculum ↓

Illustration of AI models and automation

Upcoming Artificial Intelligence batches

Contact LearnAI for the next batch. Ask on WhatsApp.

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22 modulesFoundations to applied learning

5 project topicsDomain practice and a capstone

3 training modesOnline · Classroom · Hybrid

Talk to LearnAIFees, duration and batch details

Understand the programme

Learn Artificial Intelligence through practical study.

Develop analytics and programming foundations, then explore machine learning, deep learning, computer vision, time series, natural language processing and chatbots. The curriculum connects Power BI, SQL, Python and data preparation with AI model building and practical project topics.

Your willingness to learn comes first

Who can join?

Build new skills or upgrade your technology knowledge. LearnAI welcomes students pursuing a degree, graduates, working professionals and learners from relevant domains.

Basic computer knowledge

Basic computer knowledge is recommended to help you participate in practical learning.

Students and professionals

Join while pursuing a degree, after graduation, or to develop skills for your relevant domain.

No prior technology knowledge required

You can begin without previous knowledge of the course technology. Bring your interest and willingness to learn.

No age limit

Learners of all ages are welcome. Learners under 18 should enrol with a parent or guardian’s consent.

What the curriculum develops

Skills you will practise.

Prepare and analyse data

Connect SQL, Python, statistics, ETL and exploratory analysis.

Build analytical reports

Practise Power BI dashboards and data storytelling.

Study machine learning models

Explore regression, classification, clustering and evaluation.

Explore neural networks and vision

Study ANN, CNN and image classification concepts.

Investigate sequences and language

Explore time series, RNN and NLP topics.

Develop conversational AI projects

Study sentiment, intent detection and chatbot workflows.

The complete learning path

Artificial Intelligence course curriculum.

Explore all 22 modules. Open a module to view its topics, and discuss the delivery plan for your batch.

01 / Analytics and programming foundations

MODULE 01Power BI & Data Visualization

Business Intelligence Basics
Power BI Desktop
Power Query
Data Modeling
DAX
Interactive Dashboards

MODULE 02SQL for Data Analytics

Database Fundamentals
SQL Queries
Filtering & Sorting
Joins
Aggregations
Reporting Queries

MODULE 03Python for Data Analytics

Python Fundamentals
NumPy
Pandas
DataFrames
Visualization
Data Manipulation

MODULE 04Statistics & Probability for Data Science

Descriptive Statistics
Probability
Distributions
Sampling
Correlation
Hypothesis Basics

MODULE 05Data Processing & ETL

Data Collection
Data Cleaning
Missing Values
Transformation
Integration
Validation

02 / Data science and analysis

MODULE 06Data Science Fundamentals & Lifecycle

Data Science Workflow
Problem Framing
Data Collection
Analysis Lifecycle
Model Thinking
Insight Generation

MODULE 07Exploratory Data Analysis

Data Profiling
Univariate Analysis
Bivariate Analysis
Trends & Patterns
Outlier Review
Insight Discovery

MODULE 08Advanced Statistics & Hypothesis Testing

Confidence Intervals
Hypothesis Testing
p-values
A/B Testing Concepts
Statistical Significance
Decision Making

MODULE 09Feature Engineering & Feature Selection

Feature Creation
Encoding
Scaling
Selection Methods
Dimensionality Reduction Concepts
Model-ready Data

MODULE 10Data Visualization & Storytelling

Dashboard Thinking
Visual Design
KPI Storytelling
Insight Communication
Reporting Structure
Business Presentation

03 / Machine learning core

MODULE 11Machine Learning Fundamentals

ML Workflow
Supervised vs Unsupervised Learning
Training & Testing
Algorithms Overview
Use Cases
Practical Understanding

MODULE 12Supervised Learning – Regression & Classification

Linear Models
Tree Models
Prediction Tasks
Classification Tasks
Evaluation Basics
Applied Use Cases

MODULE 13Unsupervised Learning – Clustering & Dimensionality Reduction

Clustering Concepts
Segmentation
Pattern Grouping
PCA Concepts
Feature Compression
Discovery of Hidden Structure

MODULE 14Model Evaluation & Hyperparameter Tuning

Train/Test Split
Cross Validation
Accuracy & Error Metrics
Precision/Recall Concepts
Hyperparameter Tuning
Model Improvement

04 / Deep learning and computer vision

MODULE 15Deep Learning Fundamentals

Neural Network Basics
Layers & Activations
Forward Propagation
Loss Functions
Backpropagation
Optimizers

MODULE 16Artificial Neural Networks – ANN

ANN Architecture
Dense Layers
Weights & Biases
Training Process
Classification Use Cases
Prediction Use Cases

MODULE 17Computer Vision Fundamentals

Image Data
Pixels & Channels
Image Preprocessing
Vision Tasks
Classification Concepts
Real-world Applications

MODULE 18Convolutional Neural Networks – CNN

Convolution Layers
Filters
Pooling
Feature Maps
Image Recognition
CNN Workflow

05 / Time series, NLP and conversational AI

MODULE 19Time Series Analysis & Forecasting

Sequential Data
Trend & Seasonality
Forecasting Concepts
Time-based Patterns
Demand Forecasting
Business Applications

MODULE 20Recurrent Neural Networks – RNN

Sequential Modeling
Hidden States
Sequence Learning
Time-step Understanding
RNN Applications
Series Prediction

MODULE 21Natural Language Processing – NLP

Text Preprocessing
Tokenization
Text Representation
NLP Tasks
Language Understanding
NLP Use Cases

MODULE 22Sentiment Analysis & Chatbot Development

Sentiment Classification
Intent Detection
Response Design
Chatbot Workflow
Basic Conversational AI
Real-world Support Bots

Your technical toolkit

Tools and technologies in the curriculum.

Power BISQLPythonNumPyPandasMatplotlibSeabornScikit-learnTensorFlowKerasOpenCVNLTKJupyterGitGitHub

Apply the learning

5 Artificial Intelligence project topics.

Ask about the learning datasets, project selection, guidance and delivery for your batch.

AI Dashboard & Insights Project

Build interactive dashboards, analyse data and share business insights.

Supervised Learning Prediction Project

Build prediction models and evaluate performance using learning datasets.

Clustering & Segmentation Project

Explore customer segmentation and interpret clusters.

Computer Vision / CNN Project

Build image classification models and study CNNs with image datasets.

Sentiment Analysis & Chatbot Capstone

Explore text sentiment, build a chatbot and integrate a final project.

Choose how you learn

Artificial Intelligence training near you and online.

Online training

Join from India, the USA, Canada, UK, Australia, New Zealand and Germany. Confirm your batch and time-zone schedule.

Classroom training

LearnAI Classroom: Dilsukhnagar, Hyderabad. Confirm this course, batch and exact address before visiting.

Hybrid training

Discuss combined online and classroom participation at your preferred branch. Confirm the delivery arrangements for your batch.

Fees, duration, prerequisites and upcoming batches are available on enquiry.

Learn with professional guidance

Experienced trainers. Practical knowledge.

Working professionalsIndustry knowledge connected to practical learning

10+ yearsRelevant professional experience within our core trainer team

Experienced trainersGuidance for concepts, tasks and project work

LearnAI’s core trainer team is supported by additional and part-time trainers. Trainer assignments and relevant experience vary by course, branch, training mode and batch availability. Experience figures refer to professional experience, not years of teaching.

For your batch’s trainer details, contact LearnAI.

Plan your next step

Career directions and learning support.

Roles to explore

Career directions listed in the brochure. Entry requirements depend on the role, employer and your background.

AI AnalystData ScientistMachine Learning EngineerAI EngineerComputer Vision EngineerNLP EngineerBusiness Intelligence AnalystPython Developer

Discuss career assistance

Ask about resume preparation, ATS compatibility, job-description matching, cover letters, interview practice, job discovery and application support. Confirm current availability and what is included with your enrolment.

Enrolled students receive access details for their applicable LearnAI learning and career assistance applications.

Ask About Career Assistance ↗

Before you enrol

Artificial Intelligence course questions.

Review the curriculum and ask for current delivery and enrolment details.

What does the LearnAI Artificial Intelligence Course cover?

The curriculum has 22 modules. Develop analytics and programming foundations, then explore machine learning, deep learning, computer vision, time series, natural language processing and chatbots. The curriculum connects Power BI, SQL, Python and data preparation with AI model building and practical project topics.

Which tools and technologies are included?

The curriculum lists Power BI, SQL, Python, NumPy, Pandas, Matplotlib, Seaborn, Scikit-learn, TensorFlow, Keras, OpenCV, NLTK, Jupyter, Git, GitHub. Ask LearnAI about software setup and any tool accounts required for your batch.

Which projects are listed?

Project topics include AI Dashboard & Insights Project, Supervised Learning Prediction Project, Clustering & Segmentation Project, Computer Vision / CNN Project, Sentiment Analysis & Chatbot Capstone. Confirm datasets, guidance and project selection with LearnAI.

Does the curriculum include deep learning, computer vision and NLP?

Yes. Modules 15 to 22 cover deep learning, ANN, computer vision, CNN, time series, RNN, NLP, sentiment analysis and chatbot development.

Can I join online from outside India?

Yes. LearnAI offers online classes for learners in India and abroad, including the USA, Canada, UK, Australia, New Zealand and Germany. Ask about Artificial Intelligence batch availability and your time-zone schedule.

Where can I attend classroom or hybrid training?

LearnAI is in Dilsukhnagar, Hyderabad. Confirm Artificial Intelligence availability, delivery mode and the exact address before visiting.

What are the fees, duration and prerequisites?

Contact LearnAI on WhatsApp at +91 93900 23585 for current fees, duration, prerequisites and batch details. Share your background and preferred training mode.

What career assistance can I ask about?

Discuss resume support, job-description matching, interview practice, job discovery and application assistance. Confirm current availability and enrolment terms with LearnAI.

Discuss your learning goals

Ready to explore Artificial Intelligence?

Share your background, preferred training mode, branch or country, and time zone.

Mon–Fri · 9 AM–7 PM IST · +91 93900 23585 · info@learnai.co.in

Chat with LearnAI ↗

What your course includes

Course charges cover

Live classes with a trainer
Doubt sessions
Assignments
Exams
Recordings
Portal access
Project assignment
Project explanation

Complimentary services

Resume writing
Mock interviews
Interview preparation
100% job assistance

Job assistance does not guarantee a job offer.

Learner experiences

Review summary: Praises practical analytical training and applying Data Science skills during an internship.

Read on Google

Artificial IntelligenceCourse at LearnAI