Learn about business analytics and its importance in the industry. Perform business analytics tasks using Microsoft Excel and create visual insights using charts and dashboards. Become proficient in business analytics with foundational statistics and techniques—an initial step in the data analytics program.
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Acquire essential skills to begin working with SQL databases. Learn about fundamental SQL concepts, including statements, conditional queries, commands, joins, subqueries, and diverse functions crucial for effective SQL database management and scalability.
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Embark on a comprehensive exploration of ETL essentials crucial for robust data analysis. Learn about systematically extracting structured/unstructured data, rule formulation, and utilizing diverse ETL tools like Nifi and Talend. Develop repository data loading expertise, distinguish between batch and real-time ETL, and efficiently manage ETL workflows for seamless data analysis.
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This course thoroughly explores creating impactful visualizations and informative dashboards using Tableau. Discover key data visualization concepts and learn to craft diverse charts that drive better business decisions. Master the construction of interactive dashboards with filters, parameters, and sets and utilize various visualization techniques, including heat maps, treemaps, and Pareto charts.
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Learn Python programming fundamentals and understand how it can be used in data analytics. Navigate Jupyter installations for hands-on learning and explore key concepts such as data types, loops, object-oriented principles, methods, attributes, and threading.
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Learn about various Python packages used in data analytics. Explore NumPy and Pandas and learn about the importance of statistics in data analytics. Understand essential concepts like data categorization, data wrangling, and data visualization. By the end of the course, you’ll gain practical skills to perform insightful data analysis, enhancing your ability to make data-driven decisions and solve complex problems efficiently.
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This course offers an in-depth exploration of generative AI models, particularly focusing on ChatGPT. Participants will acquire comprehensive knowledge of foundational generative AI principles, including prompt engineering, explainable AI, conversational AI, ChatGPT, and other extensive language models.
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This course will uncover the pivotal role of generative AI in data analytics, including its capabilities in generating synthetic data, enhancing visualizations, and finding hidden insights. Harness its potential to optimize ETL processes, improve forecasting accuracy, and tackle integration challenges. Delve into future trends and ethical considerations to comprehensively view generative AI’s impact. The curriculum spans data augmentation, visualization, and forecasting, offering a comprehensive understanding of how generative AI intersects with data analytics.
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Upon completing the DA and GenAI courses, participants embark on a capstone project to apply their newly acquired skills. Guided by mentors, they will apply their skills in Excel, Python, SQL, Tableau, and more to a real-world project by solving data-related challenges. This project marks the culmination of their learning journey and provides an opportunity to showcase their abilities to potential employers in a real-world context.
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