-I participated in a virtual internship offered by Accenture through the Forage platform, where I gained hands-on experience in utilizing advanced Excel functions, particularly focusing on formulas like VLOOKUP for data retrieval and processing. -During the internship, I worked on real-time data processing tasks, gathering and consolidating data from multiple files into a single, cohesive dataset. -After organizing the data, I applied my analytical skills to create interactive dashboards, providing clear and actionable insights into key business metrics. -This experience enhanced my ability to manage and analyze large datasets effectively, reinforcing the practical application of Excel in solving complex business challenges.

- I developed a deep learning model utilizing Convolutional Neural Networks (CNNs) to automate the classification process in a PLC (Programmable Logic Controller) machine, distinguishing between damaged and undamaged parts. - Using the TensorFlow library, I carefully defined various layers of the CNN architecture, including convolutional layers for feature extraction, pooling layers for dimensionality reduction, and the output layer for final classification. -After training the model on a labeled dataset of parts, I achieved an accuracy of 90%, significantly improving the machine's ability to automatically detect and differentiate between damaged and undamaged components. -This automation enhanced the efficiency and reliability of the quality control process within the production line.

-I developed machine learning models to accurately classify between left eyes and right eyes, utilizing advanced algorithms such as the Support Vector Machine (SVM) classifier and the Decision Tree classifier. -To facilitate this, I used Python as the programming language and leveraged key libraries including Numpy for numerical computations, Pandas for data manipulation, and Matplotlib for data visualization. -These tools helped in preprocessing the dataset, conducting exploratory data analysis, and uncovering key insights. -After training and testing the models, I successfully achieved a classification accuracy of 93%, demonstrating the effectiveness of the chosen approach in distinguishing between left and right eyes.

-I Utilized SQL queries to extract relevant data from the company’s database, ensuring that the information retrieved was accurate and aligned with the specific business requirements.-Once the data was extracted, I proceeded to analyze it in Power BI, where I developed comprehensive dashboards to visualize key sales metrics.-Through these dashboards, I uncovered important insights into sales trends, performance, and customer behavior. -I then provided actionable recommendations on how to improve sales processes and strategies, identifying areas of opportunity to boost overall sales performance. My analysis and suggestions aimed at enhancing business decision-making and driving revenue growth.