Data Science

Data Science is one of the most in-demand fields of the digital age, combining the power of statistics, programming, and domain knowledge to turn raw data into meaningful insights. This course provides a comprehensive introduction to the concepts, tools, and techniques used by data scientists to analyze data, build predictive models, and make data-driven decisions. Throughout the course, learners will gain hands-on experience with essential tools such as Python, Pandas, NumPy, Matplotlib, Scikit-Learn, and SQL. The course covers the entire data science pipeline—data collection, cleaning, visualization, analysis, machine learning, and communication of results. By the end of this course, you will have the skills to solve real-world problems using data, create predictive models, and present insights effectively for decision-making. Whether you aim to start a career in data science, strengthen your analytical skills, or apply data-driven strategies to your business, this course will equip you with the knowledge and confidence to succeed. ✅ What You’ll Learn Fundamentals of data analysis and statistics Python for data science (NumPy, Pandas, Matplotlib, Seaborn) Data wrangling and cleaning techniques Exploratory Data Analysis (EDA) and visualization Supervised & unsupervised machine learning models Model evaluation and performance tuning SQL for querying and managing databases Communicating insights through dashboards and reports

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