Transform your data analysis workflow at your own pace with the power of artificial intelligence. This self-paced course explores AI tools that automate data collection, preparation, analysis, and visualization, helping you uncover meaningful insights without needing extensive coding experience. Students will be able to apply AI-driven analytics across industries such as finance, marketing, and healthcare, and clearly communicate results through visualizations and reports.
Through structured, on-demand modules, you will work through the core stages of AI-powered data analytics, starting with an introduction to AI tools and progressing through data collection, cleaning, and preprocessing. You will also explore exploratory analysis, predictive modeling, and advanced techniques such as natural language processing and time series forecasting.
What You Will Learn
- Get an overview of widely used AI tools and platforms such as IBM Watson, Google AI, Tableau, and Microsoft Azure AI
- Learn how to automate data cleaning and manage missing values and outliers using AI-powered tools
- Use AI to generate summary statistics, create visualizations, and uncover patterns in data
- Understand regression, classification, and clustering, and apply AI tools to build and evaluate predictive models
- Explore natural language processing for text analysis and automated time series forecasting with AI tools
Course Outline
Introduction to AI in Data Analytics
Overview of AI & Data Analytics
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Understanding AI and its applications in data analytics
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Benefits of using AI for data analysis
Introduction to AI Tools
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Overview of popular AI tools and platforms (e.g. IBM Watson, Google AI, Tableau, Microsoft Azure AI)
Data Collection & Preparation
Data Sources & Collection Methods
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Identifying various data sources
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Using AI tools to collect data from different platforms
Data Cleaning & Preprocessing
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Automated data cleaning techniques
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Handling missing data and outliers using AI tools
Exploratory Data Analysis (EDA)
Understanding Your Data
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Using AI tools to generate summary statistics
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Visualizing data distributions and relationships
Advanced EDA Techniques
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Automated pattern and trend detection
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AI-driven feature selection and engineering
Data Visualization
Creating Visualizations
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Using AI tools to create charts, graphs, and dashboards
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Best practices for data visualization
Interactive Dashboards
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Building interactive dashboards with AI tools
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Customizing dashboards to meet specific needs
Predictive Analytics & Modeling
Introduction to Predictive Modeling
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Understanding regression, classification, and clustering
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Using AI tools to build predictive models
Model Evaluation & Validation
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Automated model evaluation techniques
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Understanding metrics and performance evaluation
Application of AI in Various Domains
Financial Data Analysis
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Case studies and applications in financial forecasting
Marketing Data Analysis
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Analyzing customer behavior and market trends
Healthcare Data Analysis
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Applications in patient data analysis and medical research
Advanced AI Techniques
Natural Language Processing (NLP)
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Using AI for text analysis and sentiment analysis
Time Series Analysis
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Automated time series forecasting with AI tools
Capstone Project
Project Planning & Execution
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Defining a project scope and objectives
Applying Learned Skills
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Using AI tools to complete a comprehensive data analysis project
Presentation & Reporting
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Presenting findings using AI-generated reports and visualizations
