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Best Data Science & AI Training in Bhubaneswar

Best Data Science & AI Training in Bhubaneswar

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Course by
infrasofTech
Duration
6 Month +
Live Projects
5+ Projects

In today’s data-driven digital economy, mastering Data Science and Artificial Intelligence has become essential for building a successful career in technology and analytics. At InfrasofTech, we offer the best Data Science & AI training in Bhubaneswar, designed to equip students and professionals with strong analytical foundations and practical industry-ready skills. Our training focuses on real-world datasets, hands-on projects, and problem-solving techniques to help learners gain confidence in transforming raw data into meaningful insights and intelligent solutions.

Our Data Science & AI course covers Python for Data Science, NumPy, Pandas, Data Visualization, Statistics, Machine Learning, Deep Learning, Natural Language Processing (NLP), Computer Vision, and Model Deployment along with real-time projects and case studies. Whether you are a beginner, a student, or a working professional aiming to upgrade your skills, our structured curriculum and expert mentors ensure you stay competitive in today’s rapidly evolving AI-powered industry. We emphasize data preprocessing, feature engineering, model building, evaluation techniques, and scalable AI solutions to prepare you for real-world challenges across industries such as healthcare, finance, e-commerce, and automation.

Learning Data Science & AI is not just about analyzing data — it’s about building intelligent systems that predict trends, automate decisions, and drive innovation. At InfrasofTech, we train you to think like a data scientist, apply AI with confidence, and transform your skills into a successful and future-ready career in the world of intelligent technology.

InfrasofTech Training Team

Key Features of Our Python Training Program

  • Industry-Recognized Course Completion Certificate
  • Weekly Doubt-Clearing Sessions (Every Sunday)
  • Free Git & GitHub Training for Version Control and Collaboration
  • Interview-Focused Questions & Answers Discussion Sessions
  • Free Aptitude, Soft Skills & Resume Building Program
  • Recorded Video Access for Revision and Flexible Learning
  • Special One-to-One Guidance for Live Project Development
  • Weekly Online Skill Assessment Tests with Detailed Notes & Feedback

Introduction to Python Full Stack Syllabus

Module 01
DATA SCIENCE & PYTHON FOUNDATION
  • Evolution of DS & AI Lifecycle
  • Python Syntax, Variables & Dynamic Typing
  • Control Flow: if-elif-else & Loops
  • Modular Programming: Functions & Lambda
  • File Handling (CSV/Text) & Exception Handling
Module 02
PROBABILITY & STATISTICS
  • Population vs Sample & Scales of Measurement
  • Descriptive Stats: Mean, Median, Std Dev, IQR
  • Probability Theory & Bayes’ Theorem
  • Distributions: Normal, Binomial, Poisson
  • Outlier Detection & Z-Score Analysis
Module 03
NUMERICAL COMPUTING WITH NUMPY
  • NumPy Ndarrays & Indexing
  • Broadcasting & Vectorized Operations
  • Mathematical & Statistical Functions
  • Array Manipulation & Slicing
Module 04
PANDAS FOR DATA MANIPULATION
  • Series, DataFrames & Data Inspection
  • Handling Missing Values & Duplicates
  • Filtering, Sorting & GroupBy Aggregation
  • Pivot Tables, Merging & Concatenation
Module 05
DATA VISUALIZATION (MATPLOTLIB & SEABORN)
  • Line, Bar, Scatter & Histograms
  • Distribution & Categorical Plots
  • Heatmaps & Correlation Matrices
  • Subplots & Aesthetic Customization
Module 06
EDA & FEATURE ENGINEERING
  • Univariate, Bivariate & Multivariate Analysis
  • Data Cleaning & Outlier Treatment
  • Encoding Categorical Variables
  • Normalization, Standardization & Scaling
  • Feature Creation & Selection Methods
Module 07
SQL FOR DATA ANALYTICS
  • RDBMS, Constraints & ER Diagrams
  • SELECT, JOINs (Inner, Left, Right, Full)
  • Aggregate Functions & Subqueries
  • Views, Indexes & Database Normalization
Module 08
WEB SCRAPING & COLLECTION
  • BeautifulSoup & HTML Parsing
  • Selenium for Dynamic & Infinite Scrolling
  • Automation Scripts for Dataset Generation
  • Multi-page Scraping & Image Collection
Module 09
BUSINESS INTELLIGENCE (POWER BI)
  • Power Query: Data Cleaning & Import
  • Data Modeling & Relationship Mapping
  • DAX Measures & Calculated Columns
  • Dashboarding & Business Storytelling
Module 10
MATH FOR MACHINE LEARNING
  • Linear Algebra: Vectors, Matrices & Eigenvectors
  • Calculus: Derivatives & Partial Derivatives
  • Cost Functions & Gradient Descent Variants
  • Optimization for Model Convergence
Module 11
SUPERVISED LEARNING (REGRESSION)
  • Simple & Multiple Linear Regression
  • Polynomial & Regularized (Lasso/Ridge)
  • Error Metrics: MSE, MAE, R-Squared
  • Decision Trees & Random Forest Regressors
  • Gradient Boosting & XGBoost Models
Module 12
SUPERVISED LEARNING (CLASSIFICATION)
  • Logistic Regression & Sigmoid Function
  • KNN, Naive Bayes & SVM Kernels
  • Evaluation: Confusion Matrix, AUC-ROC
  • Pruning & Interpretability in Trees
  • Ensemble Methods: Bagging & Boosting
Module 13
UNSUPERVISED LEARNING
  • K-Means, Hierarchical & DBSCAN Clustering
  • Dimensionality Reduction: PCA
  • Explained Variance & Feature Compression
  • Visualization of High-Dimensional Data
Module 14
DEEP LEARNING & NEURAL NETWORKS
  • Perceptrons & Multi-Layer Perceptrons (MLP)
  • Activation Functions: ReLU, Sigmoid, Tanh
  • CNNs for Image Processing
  • RNNs, LSTMs & GRUs for Sequences
Module 15
NLP & GENERATIVE AI
  • Tokenization, Lemmatization & spaCy
  • Transformer Architecture & Attention
  • LLMs (GPT, LLaMA) & Hugging Face
  • Prompt Engineering & Chatbot Building
Module 16
MLOPS & DEPLOYMENT
  • Model Lifecycle: Train, Validate, Monitor
  • CI/CD/CT (Continuous Training) Pipelines
  • REST APIs with FastAPI & Flask
  • Docker Containerization & Kubernetes
  • Cloud: AWS SageMaker, Azure ML, Vertex AI

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