Artificial Intelligence
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Become an Artificial Intelligence Expert – Learn AI from Cyber Core Technologies
Artificial Intelligence (AI) course is designed for students, professionals, and tech enthusiasts who want to gain real-world AI skills and build a successful career in one of the fastest-growing industries.
Whether you're a beginner or have some experience in machine learning, our AI training program offers a structured, practical approach to help you understand and apply artificial intelligence in various domains.
Industry-Focused Curriculum
Hands-On Training with Real Projects
Expert Faculty & Mentorship
Globally Recognized Certification
Career Support & Placement Assistance
Flexible Learning Modes
SALARY PACKAGE
AVERAGE JOBS IN INDIA
IN-DEMAND JOB
BILLIONS ($) INDUSTRY
Cyber Core Technologies
Why You Should Learn Artificial Intelligence
Artificial Intelligence (AI) is no longer just a futuristic concept — it’s shaping the world we live in today. From self-driving cars and voice assistants to personalized recommendations and advanced healthcare, AI is transforming industries and creating new career opportunities. Here’s why learning AI is one of the smartest decisions you can make right now.
Why Choose
Artificial Intelligence Course?
Comprehensive Curriculum
Covers Machine Learning, Deep Learning, Natural Language Processing (NLP), Neural Networks, and more.
Experienced Instructors
Learn from AI professionals with real-world project experience.
Hands-on Projects
Work on real-life datasets and build AI models that solve real problems.
Career Guidance & Certification
Get certified and receive placement support for AI roles in top companies.
Flexible Learning Options
Classroom & Online batches available.
Certification + Portfolio = Job Ready
Build a portfolio of real analytics projects to showcase your skills.
Who Can Join
Who Can Join Artificial Intelligence Course?
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Are you ready to start your course
Artificial Intelligence Course Modules
What You’ll Learn in Artificial Intelligence
Week 1: Introduction to AI & Python for AI
🎯 Goal: Understand basic AI concepts & get comfortable with Python.
Topics:
What is AI? History, types (Narrow, General, Super AI)
Applications of AI (healthcare, finance, robotics, etc.)
Intro to Machine Learning (ML) vs. AI vs. Deep Learning (DL)
Basic Python for AI:
Variables, data types, control flow
Functions, lists, dictionaries
Numpy & Pandas basics
Hands-On:
Set up Python (Anaconda or Jupyter)
Load datasets using Pandas
Do simple data manipulations
Week 2: Machine Learning Basics
🎯 Goal: Learn the foundations of supervised and unsupervised learning.
Topics:
Supervised vs. Unsupervised learning
Regression (Linear Regression)
Classification (Logistic Regression, KNN)
Clustering (K-Means)
Evaluation metrics (accuracy, precision, recall, F1)
Hands-On:
Use Scikit-learn for linear & logistic regression
Build a simple classification model on real-world data (e.g., Titanic dataset)
Week 3: Neural Networks & Deep Learning
🎯 Goal: Understand how neural networks work and build simple models.
Topics:
What are Neural Networks? Perceptron, activation functions
Intro to TensorFlow or PyTorch
Deep Learning: MLP, CNN, RNN (basic understanding)
Overfitting and regularization (dropout, L2)
Hands-On:
Build a basic neural network using Keras/TensorFlow
Classify MNIST digits (handwritten numbers)
Tools:
TensorFlow + Keras (beginner-friendly)
Google Colab for training models in the cloud
Week 4: AI Applications & Projects
🎯 Goal: Apply your skills to real-world problems.
Topics:
Natural Language Processing (NLP): Tokenization, sentiment analysis
Computer Vision basics: Image classification with CNNs
Ethics in AI: bias, fairness, transparency
Introduction to Generative AI (ChatGPT, DALL·E)
Projects:
Sentiment analysis on movie reviews
Image classifier for basic categories (cats vs dogs)
Small chatbot using pre-trained models
Showcase:
Build a portfolio on GitHub
Write a Medium or blog post summarizing your learning
Cyber Core Advantage
Career Opportunities After This Course
Completing an Artificial Intelligence course opens the door to some of the most in-demand and high-paying careers in the tech industry.
AI Engineer
Data Scientist
AI Research Scientist
Computer Vision Engineer
Natural Language Processing (NLP) Engineer
AI Product Manager
Robotics Engineer
Big Data Engineer / AI Data Engineer
AI Ethicist / Policy Advisor
Business Intelligence Analyst (with AI skills)
Cyber Core Technologies
Tools & Platforms You'll Learn
Python
Core language for AI
Jupyter Notebook
Interactive development
TensorFlow
Build neural networks
PyTorch
Research & deployment
Scikit-learn
Classical ML models
Pandas
Data wrangling
Matplotlib
Plotting and graphs
Hugging Face
Pre-trained models
Docker
Package & deploy AI apps
Google Colab
Free GPU-powered notebook
Career Services
Helping you become industry ready
mock interviews
Get ready for interviews by practising in mock sessions with industry experts
Resume building
Get personalised inputs on improving your resume
placement assistance
Get ready for interviews by practising in mock sessions with industry experts
Industry mentor sessions
Connect with top talent working to get career and project guidance
Feedback from Students
Cyber Core Technologies has trained more than 18,000 aspirants so far and the figure is steadily increasing with time.
Behind the word mountains from the countries Vokalia and Consonantia, there live the blind. texts. Separated they.
BEFORE YOU ASK
Here’s what you need to know
A small river named Duden flows by their place and supplies it with the necessary regelialia. It is a paradise
Anyone with an interest in AI can join! Some courses require basic programming or math skills, but many beginner courses start from scratch.
Most AI courses recommend knowing basic programming, especially Python, since it’s the main language used in AI and ML projects.
Basic knowledge of linear algebra, calculus, probability, and statistics helps but many courses teach these concepts as needed.
It varies:
Short intro courses: a few weeks (10-20 hours)
Comprehensive courses or nanodegrees: 3-6 months or more (part-time)
Introduction to AI and ML concepts
Data preprocessing and visualization
Supervised and unsupervised learning algorithms
Neural networks and deep learning basics
Practical projects and real-world applications
Good courses include practical exercises, coding assignments, and projects to apply what you learn.
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