AI+ Data
The AI+ Data Course provides a comprehensive foundation in data science, covering key topics such as statistical analysis, data wrangling, and machine learning. Explore the latest AI data training techniques, including generative AI tools and advanced machine learning. Master data storytelling and decision-making to drive impactful business insights. This AI+ Data Training program is ideal for data professionals looking to enhance their expertise in AI-driven solutions for real-world applications.
All students receive:
- One-Year Subscription (with all updates)
- High-Quality E-Book
- Al Mentor for Personalized Guidance
- Quizzes, Assessments, and Course Resources
- Exam Study Guide
- Proctored Exam with one Free Retake
Check out our full list of training locations and learning formats. Please note that the location you choose may be an Established HD-ILT location with a virtual live instructor.
Train face-to-face with the live instructor.
Access to on-demand training content anytime, anywhere.
Attend the live class from the comfort of your home or office.
Interact with a live, remote instructor from a specialized, HD-equipped classroom near you. An SLI sales rep will confirm location availability prior to registration confirmation.
All Sunset Learning dates are guaranteed to run!
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Prerequisites:
Required:
- 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.
Recommended:
- AI+ Executive or AI+ Everyone
Target Audience:
- Database Analyst
- Data Analyst
- Database Technician
- Power BI Data Analyst
- IT Professional
Course Objectives:
- Acquire a strong foundation in data science fundamentals, including an overview of the field, its project lifecycle, and essential statistical principles.
- Develop proficiency in handling and processing data by learning about various data types, storage technologies, and methods for data wrangling, imputation, and transformation.
- Enhance analytical capabilities through exploratory data analysis using data visualization tools and techniques, and explore the use of Generative AI for deeper insights.
- Master machine learning by understanding and applying both supervised and unsupervised algorithms, and explore complex problem-solving through advanced techniques like clustering and ensemble learning.
- Apply data-driven decision-making and storytelling skills in real-world scenarios, learning to extract and communicate insights effectively, culminating in a capstone project focused on employee attrition prediction.
Course Outline:
Foundations of Data Science
- Introduction to Data Science
- Data Science Life Cycle
- Applications of Data Science
Foundations of Statistics
- Basic Concepts of Statistics
- Probability Theory
- Statistical Inference
Data Sources and Types
- Types of Data
- Data Sources
- Data Storage Technologies
Programming Skills for Data Science
- Introduction to Python for Data Science
- Introduction to R for Data Science
Data Wrangling and Preprocessing
- Data Imputation Techniques
- Handling Outliers and Data Transformation