Ayesha Majeed

Python For Data Analysis https://www.mygreatlearning.com/ Dec 2023 Mastered the use of Python libraries such as Pandas and NumPy for handling and analyzing data.Successfully performed data cleaning, transformation, and aggregation tasks to prepare datasets for further analysis.Developed the ability to create insightful visualizations using Matplotlib and Seaborn.Created various types of charts and graphs to effectively communicate data trends and patterns.Conducted thorough exploratory data analysis to summarize data characteristics and… Show more Mastered the use of Python libraries such as Pandas and NumPy for handling and analyzing data.Successfully performed data cleaning, transformation, and aggregation tasks to prepare datasets for further analysis.Developed the ability to create insightful visualizations using Matplotlib and Seaborn.Created various types of charts and graphs to effectively communicate data trends and patterns.Conducted thorough exploratory data analysis to summarize data characteristics and identify key features.Applied statistical techniques and visualizations to understand data distributions and relationships.Addressed common data quality issues such as missing values, outliers, and inconsistencies.Implemented preprocessing steps to ensure data was suitable for analysis and machine learning applications.Utilized statistical methods for hypothesis testing, correlation analysis, and regression modeling.Interpreted statistical results to draw meaningful conclusions and support data-driven decision-making.Gained experience in advanced topics such as time series analysis, feature engineering, and data wrangling.Applied machine learning techniques for predictive analysis and modeling, enhancing the depth of data insights.Applied learned skills to real-world projects and case studies, demonstrating the ability to analyze complex datasets.Presented findings and insights effectively through reports and visualizations.Python: Programming language for data analysis.Pandas: For data manipulation and analysis.NumPy: For numerical operations and array handling.Matplotlib/Seaborn: For data visualization.Jupyter Notebooks: For interactive analysis and documentation. Show less

Python For Data Science https://www.mygreatlearning.com/ Dec 2023 Mastered the basics of Python programming, including data types, control structures, and functions.Developed the ability to write clean, efficient, and Pythonic code.Utilized Python libraries such as Pandas and NumPy for data cleaning, manipulation, and exploration.Handled large datasets, perform aggregations, and conduct exploratory data analysis (EDA).Created compelling visualizations using Matplotlib, Seaborn, and Plotly to represent data effectively.Developed skills to… Show more Mastered the basics of Python programming, including data types, control structures, and functions.Developed the ability to write clean, efficient, and Pythonic code.Utilized Python libraries such as Pandas and NumPy for data cleaning, manipulation, and exploration.Handled large datasets, perform aggregations, and conduct exploratory data analysis (EDA).Created compelling visualizations using Matplotlib, Seaborn, and Plotly to represent data effectively.Developed skills to interpret and present data insights through charts, graphs, and interactive plots.Applied statistical methods for analyzing data, including hypothesis testing, correlation analysis, and regression techniques.Interpreted statistical results to make data-driven decisions and draw meaningful conclusions.Implemented machine learning algorithms using Scikit-learn for classification, regression, and clustering tasks.Developed and evaluated models, perform feature selection, and apply techniques like cross-validation and hyperparameter tuning.Explored advanced topics such as natural language processing (NLP), time series analysis, and deep learning.Utilized libraries like TensorFlow or Keras for developing and training neural networks.Applied theoretical knowledge to real-world projects and case studies, showcasing the ability to solve data science problems.Presented findings and insights through detailed reports and visualizations.Tools and Technologies Used:Python: Core programming language for data science tasks.Pandas: For data manipulation and analysis.NumPy: For numerical computations and array handling.Matplotlib/Seaborn/Plotly: For creating visualizations.Scikit-learn: For machine learning algorithms and model evaluation.Jupyter Notebooks: For interactive coding, analysis, and documentation.TensorFlow/Keras: For deep learning and neural network applications. Show less

IELTS Successful Applicant British Council Jul 2022

Certification for conducting one day webinar on SEO - Arranged by IEEE Society

Certification in Big Data Analytics - Conducted by Professor Dr. S. Ejaz Ahmed (Brock University, Canada)

Participated in Virtual workshops - Conducted by Nestle