In this course, you will learn
- The entire toolbox you need to become a data scientist.
- Fill up your resume with in demand data science skills: Statistical analysis, Python programming with NumPy, pandas, matplotlib, and Seaborn, Advanced statistical analysis, Tableau, Machine Learning with stats models and scikit-learn, Deep learning with TensorFlow.
- Impress interviewers by showing an understanding of the data science field.
- Learn how to pre-process data.
- Understand the mathematics behind Machine Learning (an absolute must which other courses don’t teach!).
- Start coding in Python and learn how to use it for statistical analysis.
- Perform linear and logistic regressions in Python.
- Carry out cluster and factor analysis.
- Be able to create Machine Learning algorithms in Python, using NumPy, statsmodels and scikit-learn.
- Apply your skills to real-life business cases.
- Use state-of-the-art Deep Learning frameworks such as Google’s TensorFlowDevelop a business intuition while coding and solving tasks with big data.
- Unfold the power of deep neural networks.
- Improve Machine Learning algorithms by studying underfitting, overfitting, training, validation, n-fold cross validation, testing, and how hyperparameters could improve performance.
- Warm up your fingers as you will be eager to apply everything you have learned here to more and more real-life situations.