Learn Data Science with Free Lessons & Tips

To excel in data science, you'll need a good grasp of several key mathematical areas: 1. **Statistics and Probability**: Understand how to summarize data, make predictions, and calculate likelihoods. Essential for analyzing data trends and making informed decisions. 2. **Linear Algebra**: Focus on operations with matrices and vectors, crucial for handling data structures in machine learning. 3. **Calculus**: Learn how changes in one variable affect another (derivatives) and the total accumulated value (integrals), important for optimizing machine learning models. 4. **Optimization Techniques**: Techniques to find the most effective solution, especially in machine learning for training models. 5. **Discrete Mathematics and Numerical Methods**: Useful for network analysis and algorithmic efficiency. Mastering these topics helps you model and solve data-related problems effectively. read less

• Data Processing Using Python Offered by Coursera. 
• Foundations of Data Science Offered by Coursera. 
• Data Science Foundations Offered by Great Learning. 
• Data Science Math Skills Offered by Duke University through Coursera. 
• High-Dimensional Data Analysis Offred by Harvard University on edX.

read less

Data science is an interdisciplinary field that involves the collection, organization, analysis, and interpretation of data to extract valuable insights and support decision-making processes. It combines elements from various disciplines such as statistics, mathematics, computer science, and domain knowledge.

read less

Study basic and advance algorithms , learn how to evaluate models and tune hyperparameters effectively using real world projects eg: scikit learn, predictive models, tensorflow, pytorch,  make new integrations,  read others code and compare it with yours, see which is more efficient, try and learn 1 new complex problems n so on..

read less