Course description

The Data Analyst: Professional Certificate in Data Analysis is a comprehensive program designed to equip learners with the essential skills required to analyze and interpret data effectively. It covers key topics such as data cleaning, data visualization, statistical analysis, and using tools like Excel, SQL, Python, and Tableau. The certificate prepares individuals for real-world data analysis tasks, making it ideal for those pursuing a career in data science, business intelligence, or analytics. With hands-on projects and expert guidance, learners gain practical experience to solve data-driven challenges and make informed decisions.

What will i learn?

• 1. Proficiency in Data Cleaning and Preparation: Ability to clean and preprocess raw data by identifying and handling missing values, outliers, duplicates, and inconsistencies. Mastery of data transformation techniques such as normalization, aggregation, and encoding. Knowledge of tools like Excel, Python (Pandas), and SQL to prepare data for analysis.
• 2. Expertise in Data Visualization: Ability to create effective visualizations using Excel, Tableau, and Python libraries (e.g., Matplotlib and Seaborn). Skills to build interactive dashboards, reports, and charts that communicate data insights clearly to stakeholders. Understanding of visualization best practices, such as choosing the right chart types and using color schemes to enhance readability.
• 3. Strong Statistical Analysis Skills: Proficiency in applying statistical methods (e.g., mean, median, standard deviation, correlation, regression) to analyze datasets. Ability to interpret data patterns, trends, and outliers and draw conclusions based on statistical tests. Understanding of how to make data-driven predictions and decisions using basic statistical models.
• 4. Mastery of SQL for Data Extraction and Manipulation: Competence in writing SQL queries to extract, manipulate, and analyze data from relational databases. Skills to perform complex queries, including joins, subqueries, aggregations, and grouping. Ability to work with databases to access large datasets and perform critical data analysis tasks.

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