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Ybi Foundation
Ybi Foundation
Not for Profit Company

  • 🚀 Build Successful Career in 2025!

    Full Stack Program

    Ai, Data Science and Analytics

    ⚡With Interview Preparation 

    Most Affordable Platform Trusted by

    3,00,000+ Learners


    📞 (+91) 966 798 7711 (Mon to Sat 10am to 7pm)

    📧 support@ybifoundation.com

    Enroll Now!

❓Just Another Certificate Program?

NO - It is a Proven Pathway Towards Success!

Why to Join Full Stack Program at Ybi Foundation?

Why to Join Full Stack Program at Ybi Foundation?

Get Ready For
​High Paying Job Roles in 2025!

According to Microsoft, 82% of leaders globally and 85% of leaders in Asia Pacific said employees will need new skills in an “AI-powered future.” 

LinkedIn added that AI has seen rapid growth in the labor market — there is 487% growth in AI talent hiring for India compared to overall hiring.

Our Learner's Placed at

⛳ Download Your Internship + Experience Certificate after Completion

🏆 Completion Certificate

✔️ Digitally Verified

✔️ Accepted in All Colleges

✔️ Accepted in Industry

✔️ Sharable on LinkedIn

📚 What You Will Learn?

 100+ Hours    50+ Projects 

Python Programming

Environment Setup: Install Python, configure Anaconda & Jupyter Notebooks, and familiarize with the interpreter workflow.
Core Data Types: Work with integers, floats, strings, and booleans.
Operators: Arithmetic Operators, Comparison Operators, Logical Operators, Assignment Operators, Bitwise Operators, Membership Operators, Identity Operators.
Container Types: Create and manipulate lists, tuples, dictionaries, and sets.
Control Flow: Implement logic using if / elif / else statements and repetition with for and while loops.
Functions: Define reusable code blocks, handle positional and keyword arguments, return values, and apply default parameters.
Machine Learning

Data Preprocessing and Feature Engineering: Handling missing data: Imputation techniques, Data normalization and standardization, Encoding categorical variables: One-hot encoding, label encoding, Feature selection and extraction: PCA, correlation analysis.
Supervised Learning: Regression and Classification problems, simple linear regression, multiple linear regression, ridge regression, logistic regression, k-nearest neighbour, naive Bayes classifier, linear discriminant analysis, support vector machine, decision trees, bias variance trade-off, cross-validation methods such as leave-one-out (LOO) cross-validation, k-folds cross-validation, multi-layer perceptron, feed-forward neural network. Ensemble models.
Unsupervised Learning: clustering algorithms, k-means/k-medoid, hierarchical clustering, top-down, bottom-up: single linkage, multiple-linkage, dimensionality reduction, principal component analysis.
Model Evaluation and Optimization: Train-test split, cross-validation, and k-fold validation, Hyperparameter tuning: Grid search, random search, Bias-variance tradeoff and overfitting, 
Deep Learning (ANN)

Neural Networks: Basics of neural networks: Neurons, layers, activation functions, Feedforward and backpropagation, Introduction to deep learning frameworks: TensorFlow, PyTorch, Loss functions and optimizers (SGD, Adam). Build a simple neural network using TensorFlow/PyTorch. Train the network on a small dataset (e.g., MNIST).
Computer Vision

Image I/O and Video Handling, Color Space Conversion, Geometric Transformations, Smoothing & Blurring, Thresholding, Morphological Operations, Edge Detection (Canny), Corner Detection (Harris, Shi–Tomasi), Keypoint Description & Matching (SIFT, SURF, ORB), Object Detection (Haar Cascades, HOG+SVM), Contour-Based Segmentation, Deep Learning Detection (YOLO), Instance Segmentation (Mask R-CNN), Convolutional Neural Networks, Transfer Learning (VGG, ResNet), Model Fine-Tuning, Pipeline Deployment & Applications
NLP and Text Analytics

Text Preprocessing (Tokenization, Stopword Removal, Stemming, Lemmatization), Language Modeling (n-grams, Neural Language Models), Word Embeddings (Word2Vec, GloVe, FastText), Sequence Modeling (RNNs, LSTMs, GRUs), Attention Mechanisms & Transformers, Part-of-Speech Tagging, Named Entity Recognition, Dependency & Constituency Parsing, Semantic Role Labeling, Text Classification, Sentiment Analysis, Topic Modeling (LDA, NMF), Machine Translation (Seq2Seq, Attention), Text Summarization, Question Answering, Dialogue Systems, Information Extraction & Relation Extraction, Text Analytics & Visualization 
SQL and Data Bases

Introduction to Databases and SQL, Relational Data Modeling & ER Diagrams, Database Schema Design & Normalization (1NF–3NF), SQL Data Definition Language (CREATE/ALTER/DROP), SQL Data Manipulation Language (INSERT/UPDATE/DELETE), Basic SELECT Queries (SELECT/FROM/WHERE/ORDER BY), Advanced SELECT (GROUP BY/HAVING/DISTINCT), Joins (INNER/LEFT/RIGHT/FULL), Subqueries & Nested Queries, Set Operations (UNION/INTERSECT/EXCEPT), Aggregate & Scalar Functions, Views, Stored Procedures & Triggers, Indexes & Query Optimization, Transactions & Concurrency Control, Security & Permissions, Introduction to NoSQL & NewSQL Databases 
Generative AI [⭐ Professional]

Introduction to Databases and SQL, Relational Data Modeling & ER Diagrams, Database Schema Design & Normalization (1NF–3NF), SQL Data Definition Language (CREATE/ALTER/DROP), SQL Data Manipulation Language (INSERT/UPDATE/DELETE), Basic SELECT Queries (SELECT/FROM/WHERE/ORDER BY), Advanced SELECT (GROUP BY/HAVING/DISTINCT), Joins (INNER/LEFT/RIGHT/FULL), Subqueries & Nested Queries, Set Operations (UNION/INTERSECT/EXCEPT), Aggregate & Scalar Functions, Views, Stored Procedures & Triggers, Indexes & Query Optimization, Transactions & Concurrency Control, Security & Permissions, Introduction to NoSQL & NewSQL Databases 
Power BI + Tableau [⭐ in Professional]

Data Connectivity & Extraction (Power Query, Tableau Data Source), Data Transformation & Modeling (Power Query M, Tableau Prep), Data Relationships & Schema Design, Calculations & Expressions (DAX Measures, Tableau Calculated Fields), Time Intelligence & Date Functions, Basic Visualizations (Charts, Tables, Maps), Advanced Visualizations (Custom Visuals, Parameter-driven Views, Level-of-Detail Expressions), Interactive Dashboards & Storytelling, Mobility & Responsive Design, Performance Optimization & Query Tuning, Publishing & Sharing (Power BI Service, Tableau Server/Online, Public Gallery), Row-Level Security & Governance, Deployment & Embedding (Power BI Embedded, Tableau Embedded Analytics), Integration with Azure/Salesforce/Databricks, Automated Refresh & Scheduling, Audit & Usage Monitoring, AI-Powered Insights (Power BI AI visuals, Tableau Explain Data)
Math and Statistics [⭐ in Professional]

Linear Algebra, Differential & Integral Calculus, Probability Theory, Descriptive Statistics, Inferential Statistics & Hypothesis Testing, Regression Analysis, Bayesian Statistics, Multivariate Statistics, Discrete Mathematics, Optimization & Numerical Methods, Time Series Analysis 
Big Data [⭐ in Professional]

SparkSession Initialization, pandas API on Spark Quickstart, DataFrame API, Series API, Index API, CategoricalIndex API, DatetimeIndex API, GroupBy & Aggregations, Window Functions, Vectorized UDFs, DataFrame↔pandas Conversion, SQL Queries & Temporary Views, DataFrame Transformations & Joins, Window Clauses & Set Operations, Performance Optimizations (broadcast joins, predicate pushdown), MLlib Data Types & Basic Statistics, Feature Extraction & Transformation (FeatureHasher, TF–IDF), Classification (Logistic Regression, Decision Trees, Random Forests), Regression (Linear Regression, Ridge Regression), Clustering (KMeans), Collaborative Filtering (ALS), Dimensionality Reduction (PCA), Model Selection & Hyperparameter Tuning (Grid Search, Cross-Validation), Pipelines API
MLOps [⭐ in Professional]

MLOps Overview & Best Practices, Cloud Provider Account & Workspace Setup (SageMaker, Azure ML, Vertex AI), Version Control & Collaboration, Data & Feature Store Management (SageMaker Feature Store, Azure Feature Store, Vertex AI Feature Store), Experiment & Model Tracking (SageMaker Experiments, Azure ML Experiments, Vertex AI Experiments)

Who Can Join Internship?

✔️ College Students

✔️ Freshers / Recent Graduates

✔️ Working Professional


B.Tech / M.Tech / BCA / MCA / BBA / MBA / Diploma and all other domains . . . open for

All Academic Years - All Branches

Why at Ybi?

Get Started Now!

Full Stack Program with Internship (Students)
​​ Onetime Payment  - Rs. 999.00

🎓 Live Training + 🔥 Live Mentor Support + 🎯 Live Project Guidance + Industry Based Projects + ⭐Completion Certificate + 🏆 Internship Certificate

Note : You can access this course for 365 day(s) with this ticket.

Enroll Now

Full Stack Program with Internship +Experience Certificate (Professionals)
​Onetime Payment  - Rs. 1999.00

🎓 Live Training + 🔥 Live Mentor Support + 🎯 Live Project Guidance + 💼 Industry Based Projects + ⚡ MLOps + 🚀Interview Preparation + 📌 PYQs of Top Companies + ✨ Quant and Aptitude Preparation + ✨ Resume Building + ⭐ Course Completion Certificate + 🏆 Experience Certificate

Note : You can access this course for 365 day(s) with this ticket.

Enroll Now