Artificial Intelligence
The Artificial Intelligence course is a practical training program that teaches children what artificial intelligence is, how it is used in everyday life, and how it works in a simple and engaging way. Students explore examples such as image recognition, voice assistants, and recommendation systems while learning logical and algorithmic thinking through simple activities. The training is based on game-oriented tasks and visual examples, helping children develop creativity, curiosity for technology, and problem-solving skills.
Our advantages
Professional Mentors
Guidance and support from experienced specialists
Practical Learning
Not just theory — hands-on experience through real projects
Modern Technologies
Python, AI, web development and other trending fields
Career Support
CV preparation, interview simulations and access to job opportunities
Curriculum
Data Structures and Algorithms with Python
- 1.What is Data Science? The study of data to extract useful insights and knowledge. Variables & Basic Operations Decision Making (if-else)&Loops Lists , Tuples, Dictionaries Functions OOP
Math for Machine Learning
- 1.NumPy Creating Arrays Operations Using NumPy NumPy Data Types Data Type Objects NumPy Array Creation & Routines NumPy Indexing & Slicing NumPy Advanced Indexing Integer Indexing Boolean Array Indexing Iterating Over Array Broadcasting Array Manipulation Mathematical Functions Visualization with Matplotlib
Data Analysis with Python
- 1.Creating Pandas Series & DataFrame Viewing Data (Top & Bottom Rows) Basic Statistical Details Pandas to NumPy Conversion Selecting Columns in a DataFrame Selecting Rows in a DataFrame (loc & iloc) Boolean Indexing in Pandas Concatenation & Merge in Pandas Join in Pandas Working with date and time using Pandas Pandas Working With Text Data Read csv using Pandas Apply a Function on the Series Aggregation Across Columns Basic Statistical Details Mean Absolute Deviation of the Series Unbiased Standard Error of the Mean Count of Unique Values in a Series Pandas Built-in Data Visualization Data Analysis and Visualization with Python/Set1 Data Analysis and Visualization with Python/Set2 Box Plot Visualization with Pandas and Seaborn Applications and Projects
Statistic
- 1.Joint, Marginal, and Conditional Probability Probability Distributions: Discrete and Continuous Bayes Theorem, Divergence, Hypothesis Testing Mean, Variance, Standard Deviation Random Variables, Covariance and Correlation Law of Large Numbers, Central Limit Theorem Statistical Significance, Resampling Methods
Machine Learning with Python
- 1.What Is Machine Learning? Types of Machine Learning Bias, Variance, Overfitting, Underfitting Data Preprocessing Feature Selection, Performance Metrics Linear Regression Logistic Regression Decision Trees,&Naive Bayes KNN (K-Nearest Neighbors) & SVM (Support Vector Machine) Random Forest Bagging& Boosting KMeans
Deep Learning
- 1.What is Deep Learning and Neural Networks? Real-life examples: speech recognition, Image recognition, games Tensorflow for Deep Learning in Python Input, Weight, Output, Hidden Layers Activation functions (ReLU, Sigmoid) explained visually Fully connected layers Loss Function Training Simple Models What is CNN? Build a MNIST digit recognition model (Python + TensorFlow) Experiment with image datasets and visualize results What is RNN and why it is used for sequences Simple examples: predicting the next number or letter in a sequence Applications and Projects
Our Top Graduates
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Our Teachers
Frequently Asked Questions
idtech is a modern learning ecosystem providing education in technology, programming, and digital skills.
You can register by filling out the form in the 'Apply' section on our website.
Our courses are suitable for both beginners and those looking to deepen their expertise.
Yes, lessons are available both online and in classrooms.