Artificial Intelligence Track

Artificial Intelligence:
Level 1

Name: Artificial Intelligence Level 1
Availability: InStock

4.9 (1,850 reviews)

Advance your AI expertise with intermediate training in model development, data processing, and algorithm optimization. Master Python for AI, supervised and unsupervised learning, NLP, computer vision, and deploy your first ML models with real-world projects.

Created by Avanteia

8,420 Total Enrolled

15 Sep 2024 Last Updated

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2 Months Duration

Certificate On Completion

Introduction

Overview

This intermediate AI course builds on foundational knowledge to deliver professional skills in model development, data processing, and algorithm optimization. You will master Python for AI, implement supervised and unsupervised learning algorithms, work with NLP and computer vision, and deploy ML models using Flask — all culminating in a capstone project of your choice.

AI Basics Tools Python Projects Logic ML Models

Goal

Learning Outcome

Design and implement intelligent AI solutions using real-time data for automation, predictive analytics, and smart decision-making across industries.

Curriculum

Syllabus

Click any module to expand and view topics and hands-on labs included.

What is AI? Types of AI (ANI, AGI, ASI)
History & Milestones
AI in Daily Life (Examples: Google, Netflix, Alexa)
Careers in AI

Hands-on Lab

AI Type Classification Career Path Mapping AI Application Research

Python Basics (Variables, Loops, Functions)
Data Types, Conditionals, OOP Overview
Working with Libraries: NumPy, Pandas
File Handling & Basic Visualization (Matplotlib)

Hands-on Lab

NumPy Array Operations Pandas Data Analysis Matplotlib Visualization

What is Data? Structured vs Unstructured
Data Preprocessing, Cleaning, Normalization
Exploratory Data Analysis (EDA)

Hands-on Lab

Data Cleaning Exercise Normalization Demo EDA on Sample Dataset

What is ML vs AI?
Supervised vs Unsupervised
Simple Algorithms: Linear Regression, KNN, Decision Trees
Model Evaluation Basics (Accuracy, Precision, Recall)

Hands-on Lab

Algorithm Comparison Model Evaluation Metric Calculation

Regression Models: Linear, Logistic
Classification Algorithms: SVM, Naive Bayes, Random Forest
Model Evaluation Metrics (Confusion Matrix, ROC, F1)

Hands-on Lab

Spam Email Classification ROC Curve Analysis Confusion Matrix Visualization

Clustering (K-means, DBSCAN, Hierarchical)
Dimensionality Reduction (PCA, t-SNE)
Applications in Customer Segmentation

Hands-on Lab

Market Basket Analysis Customer Segmentation PCA Visualization

Text Preprocessing (Tokenization, Stop Words, Stemming)
Bag of Words, TF-IDF
Sentiment Analysis Basics

Hands-on Lab

Twitter Sentiment Analyzer TF-IDF Implementation Text Preprocessing Pipeline

Image Representation & Preprocessing
Edge Detection, Feature Extraction
Intro to CNNs (Conceptual)

Hands-on Lab

Face Detection using OpenCV Edge Detection Demo Feature Extraction Exercise

Saving & Loading Models (Pickle, Joblib)
Intro to Flask for AI Apps

Hands-on Lab

Deploy ML Model Locally Flask API Creation Model Serialization

Choose 1 Project:
- Customer Churn Prediction
- Movie Recommendation System
- Fake News Detection

Hands-on Lab

End-to-End Project Build Model Training & Evaluation Deployment & Documentation

Results

What You Will Learn

ML Model Development

Build and evaluate supervised and unsupervised learning models with proper metrics and validation.

NLP & Computer Vision

Implement text preprocessing, sentiment analysis, and image recognition with OpenCV and CNN concepts.

Model Deployment

Save, load, and deploy ML models locally using Flask and serialization tools like Pickle and Joblib.

Real-World Projects

Complete a capstone project in churn prediction, recommendation, or fake news detection from scratch.

Testimonials

What Our Students Say

The Level 2 course took my skills to a professional level. The Active Directory labs and privilege escalation modules are exactly what I needed to land my first pentesting job. Avanteia's hands-on approach is unmatched.

Vikram Patil Penetration Tester, Mumbai

I completed the Beginner course first and immediately enrolled in Intermediate. The malware analysis and reverse engineering modules were eye-opening. The 2-month duration is perfect for working professionals.

Sneha Kadam Cybersecurity Analyst, Pune

The cloud security and wireless hacking modules are incredibly relevant. I used the skills from this course to secure my company's AWS infrastructure. Highly recommended for anyone serious about cybersecurity.

Rahul Menon Security Engineer, Bangalore

Artificial Intelligence Level 1

Artificial Intelligence:Level 1

Overview

Learning Outcome

Syllabus

What You Will Learn

ML Model Development

NLP & Computer Vision

Model Deployment

Real-World Projects

What Our Students Say

Ready to Level Up YourCybersecurity Career?

Artificial Intelligence:
Level 1

Ready to Level Up Your
Cybersecurity Career?