AI+ Data™
# AC-120
Mastering AI, Maximizing Data: Your Path to Innovation
- 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
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.
Course + Exam Overview
Program Name
AI+ Data™
Included
Instructor-led OR Self-paced course + Official exam + Digital badge
Duration
Instructor-Led: 5 days (live or virtual) Self-Paced: 30 hours of content
Prerequisites
Basic knowledge of computer science and statistics, data analysis, fundamental AI/ML concepts, Python and R.
Exam Format
50 questions, 70% passing, 90 minutes, online proctored exam
Delivery
Online labs, projects, case studies
Outcome
Industry-recognized credential + hands-on experience
Who Should Enroll?
- 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.
Available Dates
Job Roles & Industry Outlook
Industry Growth: Fueling Data-Driven Decision Making Across All Industries
- The global AI data science market is projected to expand at a CAGR of 37.4% from 2023 to 2030. (Source: Grand View Research)
- AI-powered data analytics is transforming industries such as finance, marketing, and retail, driving innovation in data processing and decision-making.
- The adoption of AI-enhanced data solutions is accelerating, with organizations utilizing AI for real-time data analysis, predictive insights
- AI-driven automation is becoming critical for data-intensive industries, streamlining processes and improving operational efficiency across sectors.
- AI in data science is revolutionizing industries like e-commerce, supply chain management, and customer service by enhancing data-driven decision-making.
Skills You’ll Gain
Data Visualization Techniques
Data Quality and Bias Mitigation
Deep Learning for Data Processing
Statistical Modeling
Big Data Technologies
What You'll Learn
Course Overview
- Course Introduction
Module 1: Foundations of Data Science
- 1.1 Introduction to Data Science
- 1.2 Data Science Life Cycle
- 1.3 Applications of Data Science
Module 2: Foundations of Statistics
- 2.1 Basic Concepts of Statistics
- 2.2 Probability Theory
- 2.3 Statistical Inference
Module 3: Data Sources and Types
- 3.1 Types of Data
- 3.2 Data Sources
- 3.3 Data Storage Technologies
Module 4: Programming Skills for Data Science
- 4.1 Introduction to Python for Data Science
- 4.2 Introduction to R for Data Science
Module 5: Data Wrangling and Preprocessing
- 5.1 Data Imputation Techniques
- 5.2 Handling Outliers and Data Transformation
Module 6: Exploratory Data Analysis (EDA)
- 6.1 Introduction to EDA
- 6.2 Data Visualization
Module 7: Generative AI Tools for Deriving Insights
- 7.1 Introduction to Generative AI Tools
- 7.2 Applications of Generative AI
Module 8: Machine Learning
- 8.1 Introduction to Supervised Learning Algorithms
- 8.2 Introduction to Unsupervised Learning
- 8.3 Different Algorithms for Clustering
- 8.4 Association Rule Learning with Implementation
Module 9: Advance Machine Learning
- 9.1 Ensemble Learning Techniques
- 9.2 Dimensionality Reduction
- 9.3 Advanced Optimization Techniques
Module 10: Data-Driven Decision-Making
- 10.1 Introduction to Data-Driven Decision Making
- 10.2 Open Source Tools for Data-Driven Decision Making
- 10.3 Deriving Data-Driven Insights from Sales Dataset
Module 11: Data Storytelling
- 11.1 Understanding the Power of Data Storytelling
- 11.2 Identifying Use Cases and Business Relevance
- 11.3 Crafting Compelling Narratives
- 11.4 Visualizing Data for Impact
Module 12: Capstone Project - Employee Attrition Prediction
- 12.1 Project Introduction and Problem Statement
- 12.2 Data Collection and Preparation
- 12.3 Data Analysis and Modeling
- 12.4 Data Storytelling and Presentation
Optional Module: AI Agents for Data Analysis
- 1. Understanding AI Agents
- 2. Case Studies
- 3. Hands-On Practice with AI Agents
Tools You’ll Master
Google Colab
MLflow
Alteryx
KNIME
Prerequisites
- Basic knowledge of computer science and statistics (beneficial but not mandatory).
- Keen interest in data analysis.
- Willingness to learn programming languages such as Python and R.
Exam Details
Duration
90 minutes
Passing Score
70% (35/50)
Format
50 multiple-choice/multiple- response questions
Delivery Method
Online via proctored exam platform (flexible scheduling)
Exam Blueprint:
- Foundations of Data Science – 5%
- Foundations of Statistics – 5%
- Data Sources and Types – 6%
- Programming Skills for Data Science – 10%
- Data Wrangling and Preprocessing – 10%
- Exploratory Data Analysis – 12%
- Generative AI Tools for Deriving Insights – 6%
- Machine Learning – 10%
- Advance Machine Learning – 10%
- Data-Driven Decision-Making – 10%
- Data Storytelling – 6%
- Capstone Project - Employee Attrition Prediction – 10%
Choose the Format That Fits Your Schedule
What’s Included (One-Year Subscription + All Updates):
- High-Quality Videos, E-book (PDF & Audio), and Podcasts
- AI Mentor for Personalized Guidance
- Quizzes, Assessments, and Course Resources
- Online Proctored Exam with One Free Retake
- Comprehensive Exam Study Guide
- Hands-on Labs
Instructor-Led (Live Virtual/Classroom)
- 5 days of intensive training with live demos
- Real-time Q&A and peer collaboration
- Led by AI Certified Trainers and delivered through Authorized Training Partners
Self-Paced Online
- ~30 hours of on-demand video lessons, e-book, podcasts, and interactive labs
- Learn anywhere, anytime, with modular quizzes to track progress
Trusted LinkedIn Reviews Posted by Our Learners
Mirza Imaduddin
B.Tech Electronics Engineering | Data Engineering Enthusiast | Research Intern @ IIT Jammu |
I am officially AI+ Data™ Self-Paced Learning Certified. Equipped to lead in the era of innovation and technology.
Samant Raj
Aspiring Data Analyst || Python || SQL || Power BI || MS Excel || Data Visualization || Data Modelling
I am officially AI+ Data™ Self-Paced Learning Certified! Equipped to lead in the era of innovation and technology!AI CERTs™
Arushi Markand
Associate Research Analyst Intern|MBA (Business Analytics)|MSc. Data Science|BSc. (Economics, Mathematics, Statistics)
Happy to share that I have recently earned a certificate in AI + DATA. Thank you for this opportunity AICERT.
Yanumula Rohith
CSE Student at VIT | FFE Scholar | AWS Certified Solution Architect Associate | Completed Advanced Data Science Specialization with IBM
I am officially AI+ Data™ Self-Paced Learning Certified! Equipped to lead in the era of innovation and technology from AI CERTs™
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Frequently Asked Questions
What are the key components of the AI+ Data™ certification?
- The certification covers Data Science Foundations, Statistics, Programming, and Data Wrangling, along with advanced subjects such as Generative AI and Machine Learning.
How does this certification prepare participants for data challenges?
- The certification provides participants with the necessary tools and skills to handle complex data challenges, such as cleaning, transforming, and analyzing data.
What are the career opportunities after completing this certification?
- Graduates of the AI+ Data™ certification program can pursue roles such as Data Scientist, Machine Learning Engineer, Data Analyst, AI Consultant, and other data-driven positions.
What skills will I gain from this certification?
- Participants will gain skills in data analysis, machine learning, data visualization, data wrangling, and predictive analytics, along with proficiency in Python and R.
Can I pursue this course while working full-time?
- Yes, the AI+ Data™ certification is designed to be flexible and can be pursued while working full-time. The course materials are available online.
