About this course

Certified Data Analytics – Course

The learning outcomes for a Certified Data Analytics course 

1. Understanding of Data Fundamentals:

   – Define and explain key concepts in data analytics, such as data types, structures, and formats.

   – Demonstrate knowledge of data collection methods and sources.

2. Data Preprocessing and Cleaning:

   – Clean and preprocess raw data to ensure its quality and suitability for analysis.

   – Handle missing data and outliers appropriately.

3. Statistical Analysis:

   – Apply statistical techniques to analyze data and draw meaningful insights.

   – Interpret descriptive statistics and inferential statistics for decision-making.

4. Data Visualization:

   – Create effective visualizations to represent data trends and patterns.

   – Utilize tools like Tableau, Power BI, or matplotlib for data visualization.

5. Database Management:

   – Understand and work with databases, including querying and manipulating data using SQL.

   – Design and implement a relational database structure.

6. Programming Skills:

   – Use programming languages such as Python or R for data analysis.

   – Develop scripts or programs to automate data-related tasks.

7. Machine Learning Concepts:

   – Introduce basic machine learning concepts and algorithms.

   – Apply machine learning techniques for predictive modeling and classification.

8. Big Data Technologies:

   – Familiarity with big data technologies like Hadoop and Spark.

   – Process and analyze large datasets efficiently.

9. Business Intelligence:

   – Apply data analytics for business decision-making.

   – Understand how data analytics contributes to business intelligence.

10. Ethical and Legal Considerations:

    – Adhere to ethical standards in handling and analyzing data.

    – Understand the legal implications and compliance requirements related to data analytics.

11. Communication Skills:

    – Communicate findings and insights effectively through reports, presentations, and visualizations.

    – Collaborate with stakeholders to understand and address their data-related needs.

12. Continuous Learning:

    – Demonstrate a commitment to continuous learning and staying updated on emerging trends and technologies in data analytics.

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