Data Analytics using AI

8,900.00 (Inc. GST)

SKU: N/A Category:

In the modern data-driven world, businesses and organizations require advanced analytical techniques to extract meaningful insights and drive strategic decision-making. This 60-hour training on Data Analytics using AI is designed to equip participants with the necessary skills in data preprocessing, exploratory data analysis (EDA), machine learning, deep learning, NLP, and Generative AI. The course covers industry-relevant tools and real-world applications, ensuring learners can leverage AI-driven analytics for business growth.
This training is ideal for data analysts, business intelligence professionals, data scientists, and AI enthusiasts who want to apply AI techniques to data analytics.

Training Objectives:

By the end of this training, participants will be able to:

  • Understand the core concepts of Data Analytics and AI
  • Perform data cleaning, preprocessing, and EDA using Python
  • Build and interpret Machine Learning models (Regression, Classification, Clustering)
  • Work with Deep Learning and NLP techniques (BERT, Hugging Face models)
  • Implement AI-powered predictive analytics for business decision-making
  • Deploy AI models using Flask and FastAPI
  • Leverage Generative AI for automated insights and reporting

Target Audience:

This program is designed for:

  • Data Analysts & Business Analysts seeking to enhance their AI capabilities
  • Data Scientists & ML Engineers looking to integrate AI into analytics
  • IT Professionals & Developers transitioning into AI-driven analytics
  • Business Intelligence Professionals who want to automate insights using AI
  • No prior AI/ML experience is required, but basic knowledge of Python and data analytics is recommended.

Prerequisites:

Participants should have:

  • Basic knowledge of Python (variables, data types, loops, and functions)
  • Understanding of basic statistics (mean, median, variance, probability)
  • Familiarity with SQL fundamentals (SELECT, WHERE, JOIN operations)
  • Knowledge of Excel for data handling (optional but helpful)
  • No prior AI/ML experience is required, but a willingness to work with AI-based tools is recommended

Training Duration & Mode:

  • Total Duration: 120 Hours (60 Hours Live Sessions + 60 Hours Hands-on Assignments)
  • Mode: Online Live
  • Tools Used: Python, SQL, Matplotlib, Seaborn, Scikit-learn, Hugging Face, Flask, FastAPI

Additional information

Centre for Summer Training

IIT Kanpur Campus, Online Live

Batch Date

Batch 1: 19th May 2025 – 25th June 2025, Batch 2: 17th June 2025 – 22nd July 2025

Curriculum

Module 1: Introduction to Data Analytics, AI & Generative AI (8 Hours)

  • Introduction to Data Analytics (2 Hours)
    • Importance & applications
    • Types of data analytics (Descriptive, Predictive, Prescriptive)
    • Role of AI in analytics
  • Data Analytics Life Cycle & Tools (2 Hours)
    • CRISP-DM framework
    • Overview of Python, SQL, and Hugging Face
  • Introduction to AI in Analytics (2 Hours)
    • AI vs ML vs DL
    • Case studies
  • Introduction to Generative AI & Its Role in Data Analytics (2 Hours)
    • What is Generative AI?
    • Applications in analytics
    • Leveraging AI for forecasting & automation

Module 2: Data Processing & Exploratory Data Analysis (EDA) (12 Hours)

  • Data Collection & Storage (2 Hours)
    • Web scraping, APIs, SQL basics
  • Data Preprocessing & Cleaning (3 Hours)
    • Handling missing values, outliers, and feature engineering
  • Exploratory Data Analysis (EDA) with Python (3 Hours)
    • Data visualization using Matplotlib & Seaborn
  • Feature Engineering & Data Transformation (4 Hours)
    • Dimensionality reduction, SMOTE, PCA

Module 3: Machine Learning for Data Analytics (18 Hours)

  • Introduction to Machine Learning (2 Hours)
    • Supervised vs Unsupervised Learning
  • Regression Models (3 Hours)
    • Linear & Multiple Regression, evaluation metrics
  • Classification Models (3 Hours)
    • Logistic Regression, Decision Trees, Random Forest
  • Clustering & Unsupervised Learning (3 Hours)
    • K-Means, Hierarchical Clustering
  • AI-powered Predictive Analytics (2 Hours)
    • Time series forecasting
  • Hands-on with Hugging Face Models (5 Hours)
    • Deploying AI models via API

Module 4: Advanced AI in Data Analytics (13 Hours)

  • Deep Learning for Analytics (3 Hours)
    • ANN, CNN, RNN
  • Natural Language Processing (NLP) with BERT & Hugging Face (5 Hours)
    • Sentiment Analysis, AI-driven text analytics
  • AI for Big Data Analytics (2 Hours)
    • Working with Hadoop & Spark
  • Model Deployment & Monitoring (3 Hours)
    • Flask & FastAPI, bias & fairness

Module 5: Business Applications, Generative AI for Data Insights & Final Project (9 Hours)

  • Leveraging Generative AI for Data Analytics & Insights (3 Hours)
    • Using ChatGPT, LLaMA, and Gemini for automated reporting
  • Final Capstone Project using AI & Generative AI (4 Hours)
    • Real-world problem-solving, project presentation
  • Industry Case Studies & Assessment (2 Hours)
    • Practical applications & wrap-up

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