AI Data Training
| Commitment | 5 Days, 7-8 hours a day. |
| Language | English |
| User Ratings | Average User Rating 4.8 See what learners said |
| Price | REQUEST |
| Delivery Options | Instructor-Led Onsite, Online, and Classroom Live |
COURSE OVERVIEW
The AI+ Data Training Certification equips professionals with vital skills for data science. It covers key concepts like Data Science Foundations, Statistics, Programming, and Data Wrangling. Participants delve into advanced topics such as Generative AI and Machine Learning, preparing them for complex data challenges. The program includes a hands-on capstone project focusing on Employee Attrition Prediction. Emphasis is placed on Data-Driven Decision-Making and Data Storytelling for actionable insights. Personalized mentorship, immersive projects, and cutting-edge resources ensure a transformative learning journey, preparing individuals for success in AI and data science.
WHAT'S INCLUDED?
- 5 days of AI Data Training with an expert instructor
- AI Data Training Electronic Course Guide
- Certificate of Completion
- 100% Satisfaction Guarantee
RESOURCES
- AI Data Training – https://www.wiley.com/
- AI Data Training – https://www.packtpub.com/
- AI Data – https://store.logicaloperations.com/
- AI Data Training – https://us.artechhouse.com/
- AI Data Training – https://www.amazon.com/
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ADDITIONAL INFORMATION
COURSE OBJECTIVES
Upon completion of this AI Data Training course, participants can:
- Advanced Data Analysis Techniques
- Learners will acquire skills in managing, preprocessing, and analyzing data using statistical methods and exploratory techniques to uncover insights and patterns.
- Programming and Machine Learning Proficiency
- Students will develop strong programming skills necessary for data science, along with foundational and advanced machine learning techniques to build predictive models.
- Application of Generative AI and Machine Learning
- Learners will learn to employ generative AI tools and machine learning algorithms to derive deeper insights from data, enhancing their analytical capabilities.
- Data-Driven Decision Making and Storytelling
- Students who goes through this course will get the ability to make informed decisions based on data analysis and effectively communicate findings through compelling data storytelling.
CUSTOMIZE IT
- We can adapt this AI Data Training course to your group’s background and work requirements at little to no added cost.
- If you are familiar with some aspects of this AI Data Training course, we can omit or shorten their discussion.
- We can adjust the emphasis placed on the various topics or build the AI Data Training course around the mix of technologies of interest to you (including technologies other than those included in this outline).
- If your background is nontechnical, we can exclude the more technical topics, include the topics that may be of special interest to you (e.g., as a manager or policymaker), and present the AI Data Training course in a manner understandable to lay audiences.
CLASS PREREQUISITES
The knowledge and skills that a learner must have before attending this AI Data Training course are:
- 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
AUDIENCE/TARGET GROUP
The target audience for this AI Data Training course:
- All
COURSE SYLLABUS
Module 1: Foundations of Data Science
- Introduction to Data Science
- Data Science Life Cycle
- Applications of Data Science
Module 2: Foundations of Statistics
- Basic Concepts of Statistics
- Probability Theory
- Statistical Inference
Module 3: Data Sources and Types
- Types of Data
- Data Sources
- Data Storage Technologies
Module 4: Programming Skills for Data Science
- Introduction to Python for Data Science
- Introduction to R for Data Science
Module 5: Data Wrangling an Preprocessing
- Data Imputation Techniques
- Handling Outliers and Data Transformation
Module 6: Exploratory Data Analysis (EDA)
- Introduction to EDA
- Data Visualization
Module 7: Generative AI Tools for Deriving Insights
- Introduction to Generative AI Tools
- Applications of Generative AI
Module 8: Machine Learning
- Introduction to Supervised Learning Algorithms
- Introduction to Unsupervised Learning
- Different Algorithms for Clustering
- Association Rule Learning with Implementation
Module 9: Advance Machine Learning
- Ensemble Learning Techniques
- Dimensionality Reduction
- Advanced Optimization Techniques
Module 10: Data-Driven Decision-Making
- Introduction to Data-Driven Decision Making
- Open-Source Tools for Data-Driven Decision Making
- Deriving Data-Driven Insights from Sales Dataset
Module 11: Data Storytelling
- Understanding the Power of Data Storytelling
- Identifying Use Cases and Business Relevance
- Crafting Compelling Narratives
- Visualizing Data for Impact
Module 12: Capstone Project – Employee Attrition Prediction
- Project Introduction and Problem Statement
- Data Collection and Preparation
- Data Analysis and Modeling
- Data Storytelling and Presentation
