Data Science Course Syllabus
100% Job Guaranteed Courses For Any Degree / Diploma Special Projects Oriented Training for Year Gap Students Please enable JavaScript in your browser to complete this form.Please enable JavaScript in your browser to complete this form.Full Name *Numbers *Email *Select Course *Select Course*Python Full StackJava Full StackC & C++Power BIDot NET TrainingManual TestingSelenium TestingUI Path TrainingRPA Automation AnywhereData ScienceAngularNode JSMEAN StackAWS DevopsAzure DevopsBig Data HadoopMachine LearningArtificial IntelligenceDeep LearningMySQLMongo DBDigital MarketingCyber SecurityDomo Training Submit Data Science Certification Course Data Science Training in Bangalore Data Science Training Institute In Bangalore Data Science has emerged as a pivotal field in today’s technology-driven world, offering valuable insights and enabling data-driven decision-making across various industries. This course aims to equip learners with a comprehensive understanding of data science fundamentals, covering essential topics such as data exploration, statistical analysis, machine learning, and data visualization. By learning these core skills, participants will be prepared to solve real-world problems and gain proficiency in using popular tools and technologies. The Data Science course syllabus is structured to provide a balanced mix of theory, practical exercises, and hands-on projects. It is ideal for aspiring data scientists, working professionals looking to enhance their analytical skills, and anyone interested in pursuing a career in data analysis. Whether you are just beginning or want to advance your knowledge, this course offers a step-by-step approach to mastering the art and science of data. Module 1: Introduction to Data Science Definition and scope of Data Science. Importance and applications of Data Science. Data Science process: from data collection to insights. Role of a Data Scientist in various industries. Ethical considerations in Data Science. Tools and technologies used in Data Science. Overview of real-world Data Science case studies. Introduction to the course structure and expectations. Module 2 : Data Acquisition and Cleaning Sources of data: structured, semi-structured, and unstructured. Web scraping and APIs for data collection. Data quality assessment and common issues. Data preprocessing techniques. Handling missing data and outliers. Data transformation and normalization. Data integration and feature engineering. Hands-on exercises using popular data manipulation libraries. Data Science Training Options Group Training One to One Training Online Training Request For Enroll Now Data Science Training In Bangalore Module 3: Exploratory Data Analysis (EDA) Importance of EDA in understanding data. Summary statistics and data visualization. Distribution analysis and histogram plotting. Correlation and scatter plots. Box plots and violin plots. Time series analysis. Interactive data visualization tools. Applying EDA to real datasets. Module 4: Machine Learning Fundamentals Basics of machine learning and its types. Supervised vs. unsupervised learning. Model representation and evaluation. Training and testing datasets. Cross-validation techniques. Overfitting and underfitting. Performance metrics: accuracy, precision, recall, F1-score, etc. Implementing simple machine learning algorithms. Module 5: Regression and Classification Linear regression and its assumptions. Polynomial regression and regularization. Logistic regression for classification. Decision trees and random forests. Support Vector Machines (SVM). Naive Bayes classifier. Model selection and hyperparameter tuning. Hands-on projects involving regression and classification. 40 + Hours Hands On Training_____________
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