Certified Data Analytics - 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.