Dinesh Yadav B.E - Computer Science Arti 3 icial Intelligence & Machine Learning | Naad Colony, Sihma, Narnaul, 123028 | (+91) 870-816-3505 | | dineshydv3505@gmail.com | | Portfolio Website | LinkedIn | GitHub | CAREER SUMMARY An experienced data analyst with a track record of successfully completing over 3 ive data analysis projects. Data analysis using Python and its libraries such as NumPy, Pandas, Matplotlib, and Seaborn requires expert knowledge of Python and its libraries. Data manipulation and visualization skills in SQL, MS Excel, and PowerBI. A strong understanding of data cleaning, transformation, modeling, and visualization techniques. Developing actionable insights from complex datasets in order to drive informed decision- making. Seeking to leverage my analytical skills and diverse toolset to contribute effectively to data-driven initiatives. EDUCATION Bachelor of Engineering in Computer Science with AI&ML, Chandigarh University, Mohali , Punjab (IND). [July, 2020 - 2024] Senior Secondary, Haryana board of education [May, 2019] SKILLS AND STRENGTHS • Programming Languages : C, C++, HTML, PHP, CSS, JavaScript, Python, Java. • Libraries & Framework : Django, Flask, ReactJS, Node.Js, Bootstrap. • Database Technologies : MySQL, MongoDB. [Elementary Pro 3 iciency] • Data Analysis : Ms Excel, PowerBI, Tableau • Languages : English, Hindi. • Soft Skills : Problem solving, Creativity, Leadership, Active listening, Adaptability, Interpersonal skills. EXPERIENCE & PROJECTS Loan Eligibility Predication : Project Link • Developed a loan eligibility prediction project using machine learning models such as Decision Tree and Naive Bayes classi 3 ication algorithms in Python. • Utilized essential data manipulation and analysis libraries including Pandas, NumPy, and Matplotlib for preprocessing and visualizing the data. • Implemented the scikit-learn library to build, train, and evaluate the Decision Tree and Naive Bayes classi 3 iers for accurate loan eligibility predictions. • Demonstrated pro 3 iciency in feature engineering, model selection, and hyperparameter tuning to enhance the predictive performance of the models. • Successfully created a comprehensive data analysis project showcasing expertise in machine learning, data preprocessing, model evaluation, and predictive analytics, highlighting a strong foundation in data science and predictive modeling. Sales Analysis : Project Link • Developed a comprehensive sales analysis project using Python within a Jupyter Notebook environment, leveraging the power of Pandas, NumPy, Matplotlib, and Scikit-learn libraries for data manipulation, analysis, visualization, and machine learning. • Utilized Pandas for data cleaning, preprocessing, and exploratory data analysis, showcasing proficiency in handling and transforming large datasets efficiently. • Employed NumPy for numerical computations and data manipulation, enhancing the project's analytical capabilities and ensuring robust data processing. • Leveraged Matplotlib for creating insightful visualizations to communicate sales trends, patterns, and insights effectively to stakeholders. Music Store Data Analysis : Project Link • Conducted a comprehensive analysis of a music store dataset using SQL and MS Excel, showcasing pro 3 iciency in data cleaning, transformation, modeling, and visualization techniques. • Utilized SQL queries to extract, 3 ilter, and aggregate relevant data from the database, demonstrating expertise in data manipulation and querying skills. • Employed MS Excel's advanced features, such as pivot tables, charts, and formulas, to perform in-depth data analysis, identify trends, and generate meaningful insights. • Transformed the cleaned and modeled data into a format suitable for visualization and reporting in PowerBI. • Created responsive and interactive reports in PowerBI, leveraging its data visualization capabilities to present insights effectively and support data-driven decision-making, highlighting strong skills in data analysis, visualization, and reporting.