Data Science course provides a comprehensive understanding of data analysis methods and technologies, covering essential concepts in Data Analytics. It begins with foundational concepts:
- Statistics
- Probability
- Data manipulation using Python or R
Students learn data wrangling, cleaning, and preprocessing techniques to prepare data for analysis, a crucial skill for a Business Analyst. The curriculum covers machine learning algorithms, neural networks, deep learning, and data visualization using tools like Matplotlib, Seaborn, and Tableau.
By the end of the Data Science course, students gain practical experience through projects and case studies, enabling them to extract meaningful insights from data, build predictive models, and make data-driven decisions in various industries, a key aspect of Data Analytics. They’re equipped with advanced skills in natural language processing, big data technologies (Hadoop and Spark), and deploying models into production, making them proficient data scientists and Business Analysts.
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