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    AnnouncementNew self-paced courses now available — explore our AI Certs-powered certifications and start learning at your own pace.AnnouncementNew self-paced courses now available — explore our AI Certs-powered certifications and start learning at your own pace.AnnouncementNew self-paced courses now available — explore our AI Certs-powered certifications and start learning at your own pace.
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    AI CERTs®
    AT-120

    AI+ Data Practitioner™

    Formerly known as AI+ Data™ Mastering AI, Maximizing Data: Your Path to Innovation

    ₹21,999

    Delivered by UpskillNexus, an AI CERTs® Authorized Training Partner.

    AI+ Data Practitioner™ certification badge

    About this certification

    Core Concepts Covered: Data Science foundations, Python, Statistics, and Data Wrangling Advanced Topics: Dive into Generative AI, Machine Learning, and Predictive Analytics Capstone Application: Solve real-world problems like employee attrition with AI Career Readiness: Develop skills for AI-driven data science roles with hands-on mentorship

    What's included

    Package

    Instructor-led OR Self-paced course + Official exam + Digital badge

    Duration

    • Instructor-Led: 5 days (live or virtual) 
    • Self-Paced: 40 hours of content

    Exam format

    50 questions, 70% passing, 90 minutes, online proctored exam

    Prerequisites

    Basic knowledge of computer science and statistics, data analysis, fundamental AI/ML concepts, Python and R.

    Course modules

    Course Overview

    1. Course Introduction Preview

    Module 1: Foundations of Data Science

    1. 1.1 Introduction to Data Science
    2. 1.2 Data Science Life Cycle
    3. 1.3 Applications of Data Science

    Module 2: Foundations of Statistics

    1. 2.1 Basic Concepts of Statistics
    2. 2.2 Probability Theory
    3. 2.3 Statistical Inference

    Module 3: Data Sources and Types

    1. 3.1 Types of Data
    2. 3.2 Data Sources
    3. 3.3 Data Storage Technologies

    Module 4: Programming Skills for Data Science

    1. 4.1 Introduction to Python for Data Science
    2. 4.2 Introduction to R for Data Science

    Module 5: Data Wrangling and Preprocessing

    1. 5.1 Data Imputation Techniques
    2. 5.2 Handling Outliers and Data Transformation

    Module 6: Exploratory Data Analysis (EDA)

    1. 6.1 Introduction to EDA
    2. 6.2 Data Visualization

    Module 7: Generative AI Tools for Deriving Insights

    1. 7.1 Introduction to Generative AI Tools
    2. 7.2 Applications of Generative AI

    Module 8: Machine Learning

    1. 8.1 Introduction to Supervised Learning Algorithms
    2. 8.2 Introduction to Unsupervised Learning
    3. 8.3 Different Algorithms for Clustering
    4. 8.4 Association Rule Learning with Implementation

    Module 9: Advance Machine Learning

    1. 9.1 Ensemble Learning Techniques
    2. 9.2 Dimensionality Reduction
    3. 9.3 Advanced Optimization Techniques

    Module 10: Data-Driven Decision-Making

    1. 10.1 Introduction to Data-Driven Decision Making
    2. 10.2 Open Source Tools for Data-Driven Decision Making
    3. 10.3 Deriving Data-Driven Insights from Sales Dataset

    Module 11: Data Storytelling

    1. 11.1 Understanding the Power of Data Storytelling
    2. 11.2 Identifying Use Cases and Business Relevance
    3. 11.3 Crafting Compelling Narratives
    4. 11.4 Visualizing Data for Impact

    Module 12: Capstone Project - Employee Attrition Prediction

    1. 12.1 Project Introduction and Problem Statement
    2. 12.2 Data Collection and Preparation
    3. 12.3 Data Analysis and Modeling
    4. 12.4 Data Storytelling and Presentation

    Optional Module: AI Agents for Data Analysis

    1. 1. Understanding AI Agents
    2. 2. Case Studies
    3. 3. Hands-On Practice with AI Agents

    Why this certification matters

    Demand for Certified Experts:

    Organizations seek certified experts who can transform complex data into actionable insights while ensuring data integrity and privacy.

    Mitigating Data and AI Risks:

    Poor handling of data and AI technologies can lead to inaccurate analysis and business risks. This certification helps professionals mitigate such challenges.

    Designing AI-Driven Data Strategies:

    Certified professionals play a crucial role in designing AI-driven data strategies that optimize performance and align with regulatory standards.

    Career Advancement:

    As AI-powered data solutions become essential for businesses, this certification provides professionals with a competitive edge in advancing their careers.

    Who should enrol

    Data Analysts & Scientists: Enhance data analysis capabilities using AI for predictive modeling and decision-making.

    Business Intelligence Professionals: Leverage AI to uncover insights, trends, and opportunities in complex data sets.

    IT Specialists & System Integrators: Implement AI-powered solutions to optimize data management and infrastructure.

    Data Engineers: Design and develop AI-driven data pipelines and architectures for scalable solutions.

    Students & New Graduates: Build valuable AI and data science skills to thrive in an increasingly data-driven world.

    Tools you'll work with

    Google ColabGoogle Colab
    MLflowMLflow
    AlteryxAlteryx
    KNIMEKNIME
    AI Data & Robotics
    AI Technical

    Interested in AI+ Data Practitioner™?

    Tell us a little about yourself and our team will get back to you with pricing, schedule and next steps.