AI+ Data Certification Course Online
Length
5 days / 5 weeks
Price
$2999
Days
Mon - Fri
Why Choose This Course
AI+ Data Certification Course is a beginner‑friendly program that teaches you how to work with data using artificial intelligence. You will learn essential data skills like data analysis, visualization, and how AI helps turn data into smart business decisions. This course is perfect for anyone who wants a recognized certification and practical skills for a data‑driven career.
It is an intelligent decision if you wish to develop your data and AI abilities but don’t want to limit yourself to one particular technology. This program will start with the fundamentals of statistics and data handling before progressing towards data exploration, machine learning, and artificial intelligence-based insights. All of this information is directly linked to the certification examination and thus guarantees success.
The target audience for this program includes anyone with some prior experience in data management or wishing to specialize in data-related tasks. Data analysts, business intelligence professionals, IT experts, and even data engineers can benefit greatly from this program.
Prerequisites
Exam
Candidates can achieve this certification by passing the following exam(s).
AI+ Data (AT-120).
Books
Flexible Delivery Options
- Live virtual online training attend in real-time from anywhere
Skills Gained
- Understand the data science lifecycle and where AI techniques add value.
- Apply foundational statistics to support analysis and interpretation.
- Identify data sources and types; recognise storage options and formats.
- Use programming skills for data science to prepare, transform, and analyse data.
- Perform data wrangling and preprocessing, including handling missing values and outliers.
- Conduct exploratory data analysis to uncover trends and patterns.
- Leverage generative AI tools to derive insights from data responsibly.
- Build and evaluate machine learning models for predictive tasks.
- Apply advanced machine learning techniques and tuning strategies.
- Translate analytics into data-driven decisions for stakeholders.
- Communicate findings through clear data storytelling and visual narratives.
- Work with commonly used tools such as Google Colab, MLflow, KNIME, and Alteryx.
Who Should Attend?
This course is ideal for data analysts and data scientists, business intelligence professionals, IT specialists and system integrators, and data engineers who want a structured, vendor-neutral path to applying AI in analytics projects.
Start your Data Science and AI journey today with Training Courses Now — call us now on 📞 1300 649 299 to enroll!
Course Schedule & Pricing
Choose the schedule that fits your life — all options include full course materials & certification support
Full-time immersion for rapid certification readiness.
Balance your career while you upgrade your skills.
Maximum flexibility for busy working professionals.
Outline
- Foundations of data science: concepts, lifecycle, and use cases.
- Statistics for analytics: descriptive measures, probability, and inference.
- Data sources and types: structured, semi-structured, unstructured; common repositories.
- Data storage options: databases and related storage technologies for analytics.
- Programming for data science: introductory Python for analysis tasks.
- Programming for data science: introductory R for analysis tasks.
- Data wrangling: imputation techniques for missing data.
- Data wrangling: handling outliers and applying transformations.
- Exploratory data analysis: profiling datasets and summarising distributions.
- Exploratory data analysis: visualisation approaches for insight discovery.
- Generative AI for insights: applying tools to augment analysis workflows.
- Machine learning fundamentals: model types and predictive pipelines.
- Model evaluation: selecting metrics and validating results.
- Advanced machine learning: ensemble and optimisation techniques.
- Data-driven decision-making: framing recommendations from analytical outcomes.
- Data storytelling: structuring narratives and visuals for stakeholders.
- Using Google Colab for notebooks and reproducible experiments.
- Experiment tracking with MLflow to manage model iterations.
- Visual workflows with KNIME for data prep and analytics tasks.
- Accelerating preparation with Alteryx for repeatable pipelines.
- Project workflow and collaboration across the analytics lifecycle.
- Capstone project: employee attrition prediction end-to-end
Terms & Conditions
Frequently Asked Questions (FAQ's)
What is AI data?
What is the AI+ Data certification and who awards it?
Is the course suitable for beginners in AI and data analytics?
What topics are covered to prepare me for the exam?
What is a Data Science and AI course?
A Data Science and AI course teaches how to collect, analyze, and use data to build smart systems. It covers skills like machine learning, statistics, Python, and real‑world AI applications.
How does training data impact an AI’s effectiveness?
Training data helps an AI learn patterns and make decisions. Better quality data makes AI more accurate, fair, and reliable.
Our Partnership
Reliable certification testing is vital for validating professional skills in today’s tech-driven world. As a Pearson VUE Authorised Centre, we provide a secure environment for globally recognised IT exams. This partnership ensures convenient access to certifications with the highest standards of integrity and accuracy.
Our Accreditations
