Data Cleaning:

• Proficient in data cleaning techniques in Python, Excel, and other data analysis tools.
• Expertise in handling missing data, duplicates, and outliers for data quality improvement.
• Skilled in data transformation and preparation for analysis and visualization.
• Experience in data validation and ensuring data consistency and accuracy.

Data Analysis and Visualization:

• Proficient in creating data visualizations and reports using Excel, Power BI, and Tableau.
• Expert at translating complex datasets into clear and actionable insights.
• Capable of designing interactive dashboards for tracking key performance indicators.
• Strong data visualization skills for effective communication.

Python:

• Proficient in Python programming for data analysis and manipulation.
• Skilled in data processing and analysis using Python libraries like Pandas, NumPy, and Matplotlib.
• Capable of building data pipelines and automating tasks using Python scripting.

Machine Learning:

• Knowledgeable in machine learning techniques and algorithms.
• Experience in developing predictive models and machine learning applications.
• Skilled in model training, evaluation, and implementation.

These bullet points showcase your skills in data cleaning, data analysis and visualization, Python, and machine learning, making it clear that you are a versatile data professional capable of handling various aspects of data-related tasks.