presentation and report on data science (it topic)

report on a it topic i.e is data science

1. IT REPORT on DATA SCIENCE NAME :YOGAL SINGH CHAUHAN COLLEGE: 21IT63 UNIV. ROLL. : 21EEAIT061 BRANCH : IT SEMESTER : 7TH SUBMITTED TO : MRS. SHIKHA GUPTA

2. Internship Overview Company : Internship-Studio Duration : 1 Month Key Areas of Learning: Python programming Statistics & Probability Data Manipulation & Wrangling Data Visualization Machine Learning

3. Key Skills Acquired Python Libraries : Pandas, NumPy, Matplotlib, Seaborn Data Handling : Data cleaning, preprocessing, feature engineering Data Visualization : Creating informative charts and graphs Machine Learning : Logistic Regression, Model evaluation techniques

4. Projects Overview Project 1 : EDA on COVID-19 Dataset Data cleaning and preprocessing Univariate and bivariate analysis Visualizing trends and insights Project 2 : Machine Learning Model (Logistic Regression) Predicting health outcomes using demographic data Model evaluation with accuracy, precision, and recall

5. Tools & Technologies Used Programming Language : Python Libraries : Pandas, NumPy, Matplotlib, Seaborn, Scikit-learn Tools : Jupyter Notebook, GitHub

6. Key Learnings Gained proficiency in data preprocessing and feature engineering. Strengthened my understanding of machine learning algorithms. Improved ability to communicate insights via data visualization. Gained practical experience in solving real-world data science problems.

7. Challenges Faced Handling missing data and outliers Model selection and tuning for optimal performance Ensuring data quality through effective wrangling

8. Recommendations Focus on foundational concepts : Statistics, Python, and ML basics Practice on diverse datasets to strengthen problem-solving skills Enhance communication through data visualization

9. Conclusion The internship provided hands-on experience and deepened my understanding of the end-to-end data science process . Prepared me for real-world applications of data analysis and machine learning.

10. Thank You