This comprehensive course on Applied Data Science and Business Analytics with Machine Learning equips learners with the essential skills and knowledge to leverage data for actionable business insights and strategic decision-making. The curriculum combines foundational programming and statistical techniques with advanced machine learning algorithms and real-world projects, preparing students to solve complex business challenges using data-driven approaches.

Starting with Python programming fundamentals, the course progressively introduces descriptive and inferential statistics, hypothesis testing, and exploratory data analysis. Students develop proficiency in data wrangling, cleaning, and visualization using popular libraries and tools. Critical statistical methods such as Chi-Square tests, ANOVA, PCA, and dimensionality reduction are deeply explored to prepare learners for practical data analysis.

The program further dives into advanced topics including data mining with clustering and decision tree algorithms, and predictive modeling encompassing regression techniques, linear discriminant analysis, and classification methods. Ensemble learning approaches like bagging, boosting, and stacking are also covered to empower students with sophisticated supervised learning skills.

A dedicated module on machine learning deepens understanding of classification techniques, SVMs, and Naive Bayes classifiers, followed by hands-on projects involving sentiment analysis and domain-specific capstones in healthcare, fintech, retail, and more. Additional-free add-on modules on deep learning architectures and deploying machine learning models ensure learners gain exposure to cutting-edge technologies and deployment best practices.

Throughout the course, learners engage with quizzes, assignments, and real-world projects to consolidate theory with practice and build a competitive portfolio. Upon completion, participants receive a certificate, validating their readiness to excel as data science and business analytics professionals with machine learning expertise.

Duration: 6 Months
Mode: Online  | 6–8 hours/week | Level: Beginner to Advanced
Tools Used: Python, Jupyter, Pandas, Scikit-learn, SQL, Tableau/ Power BI, Git, PyTorch