What you will learn in Introduction to Artificial Intelligence (AI) Course
- Gain hands-on experience with tools like spreadsheets, SQL, and R to manipulate and analyze data effectively.
- Learn data cleaning techniques to ensure accuracy and reliability in decision-making.
- Explore exploratory data analysis methods to uncover trends, patterns, and insights.
- Develop data visualization skills using Tableau and ggplot2 to present findings clearly.
- Work on real-world case studies to gain practical problem-solving experience.
- Complete a capstone project, applying data analytics skills to a full-scale project.
Program Overview
Foundations of Data Analytics
⏱️ 4-6 weeks
- Introduction to the data life cycle and its role in decision-making.
- Learn problem-solving and critical thinking skills for analytics.
- Understand data analytics applications across industries.
- Get familiar with tools like spreadsheets, SQL, and visualization software.
Data Cleaning and Preparation
⏱️6-8 weeks
- Learn data structures and databases for efficient data storage.
- Use spreadsheets and SQL to clean and manipulate data.
- Identify common data errors and apply cleaning techniques.
- Ensure data accuracy and consistency for reliable analysis.
Data Analysis with Spreadsheets, SQL, and R
⏱️8-12 weeks
- Perform calculations, filtering, and pivot tables in spreadsheets.
- Write SQL queries to retrieve and manipulate data.
- Use R programming for statistical analysis and visualization.
- Develop data-driven business recommendations.
Data Visualization and Storytelling
⏱️10-12 weeks
- Create visual dashboards using Tableau and spreadsheets.
- Translate complex data into clear insights for stakeholders.
- Develop engaging data narratives to support decision-making.
- Apply best practices for designing effective visuals.
Google Data Analytics Capstone Project
⏱️12-15 weeks
- Work with a dataset to clean, analyze, and visualize insights.
- Present findings using dashboards, reports, and storytelling techniques.
- Apply problem-solving skills to real-world business challenges.
- Earn your Google Data Analytics Professional Certificate upon completion.
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Job Outlook
- Projected 25% job growth for data analysts by 2030 (U.S. Bureau of Labor Statistics).
- High demand across industries like finance, healthcare, tech, and e-commerce.
- Entry-level salaries range from $60K – $85K, with experienced analysts earning $90K – $120K+.
- Employers seek expertise in SQL, Python, R, data visualization, and machine learning.
- Certification improves visibility on LinkedIn and job platforms.
- Strong foundation for careers in data analytics, machine learning, and AI.
- High job security and growth potential with trends in big data, cloud computing, and AI adoption.
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Related Courses
Introduction to AI Course – Start your journey in artificial intelligence with foundational concepts and practical applications.
IBM AI Developer Professional Certificate Course – Gain hands-on experience building AI solutions with real-world projects and tools used by industry professionals.
IBM AI Foundations for Business Specialization Course – Learn how AI can transform business processes and drive strategic decisions.
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What Is Python Used For – Understand why Python is a cornerstone language for AI development and data science applications.
Specification: Introduction to Artificial Intelligence (AI) Course
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FAQs
- Start with foundational concepts: what AI is, its types (e.g., machine learning, generative AI), and real-world use cases.
- Understand common AI domains: NLP, computer vision, robotics.
- Learn ethical basics: AI governance, responsible use, bias and fairness.
- Choose beginner-friendly courses that include modules, hands-on labs, and projects.
- Yes—platforms like Coursera often offer free trials, with full access via subscriptions (~$39–$49/month).
- Some foundational courses require minimal time commitment (e.g., 7 hours over 3 weeks).
- Esteemed educators such as Andrew Ng (AI for Everyone) provide highly rated options.
- AI terminology and subfields: machine learning, neural networks, deep learning, generative AI.
- Application domains: NLP, computer vision, robotics across industries.
- Ethics, responsible AI, and governance: fairness, transparency, societal impact.
- Hands-on labs and introductory projects to see AI in action
- Many beginner AI courses are short—ranging from a few hours to a month (e.g., 7 hours over 3 weeks).
- Subscription-based pricing ($39–$49/month) makes even longer programs affordable if completed in under 2–3 months.
- Shorter courses can still deliver significant foundational knowledge and skills quickly.
