This app is an excellent choice for beginners to learn Data Science through interactive video tutorials and lessons for free.

Also, this app doesn't require any signup process which makes it extremely user-friendly and convenient to use.

★ What you'll learn in this course? ★
1. The course provides the entire toolbox you need to become a data scientist
2. Fill up your resume with in demand data science skills
3. Learn Statistical analysis, Python programming with NumPy, pandas, matplotlib, and Seaborn
4. Learn Advanced statistical analysis, Tableau, Machine Learning with stats models and scikit-learn, Deep learning with TensorFlow
5. Impress interviewers by showing an understanding of the data science field
6. Understand the mathematics behind Machine Learning
7. Start coding in Python and learn how to use it for statistical analysis
8. Perform linear and logistic regressions in Python
9. Be able to create Machine Learning algorithms in Python, using NumPy, statsmodels and scikit-learn
10. Apply your skills to real-life business cases
11. Use state-of-the-art Deep Learning frameworks such as Google’s TensorFlow
12. Develop a business intuition while coding and solving tasks with big data
13. Unfold the power of deep neural networks
14. Improve Machine Learning algorithms by studying underfitting, overfitting, training, validation
15. Warm up your fingers as you will be eager to apply everything you have learned here to more and more real-life situations
16. Become a Data Scientist and get hired
17. Master Machine Learning and use it on the job
18. Deep Learning, Transfer Learning and Neural Networks using the latest Tensorflow 2.0
19. Use modern tools that big tech companies like Google, Apple, Amazon and Meta use
20. Present Data Science projects to management and stakeholders
21. Learn which Machine Learning model to choose for each type of problem
22. Real life case studies and projects to understand how things are done in the real world
23. Learn best practices when it comes to Data Science Workflow
24. Implement Machine Learning algorithms
25. Learn how to program in Python using the latest Python 3
26. How to improve your Machine Learning Models
27. Learn to pre process data, clean data, and analyze large data.
28. Build a portfolio of work to have on your resume
29. Developer Environment setup for Data Science and Machine Learning
30. Supervised and Unsupervised Learning
31. Machine Learning on Time Series data
32. Explore large datasets using data visualization tools like Matplotlib and Seaborn
33. Explore large datasets and wrangle data using Pandas
34. Learn NumPy and how it is used in Machine Learning
35. A portfolio of Data Science and Machine Learning projects to apply for jobs in the industry with all code and notebooks provided
36. Learn about Data Engineering and how tools like Hadoop, Spark and Kafka are used in the industry
37. The entire Data Science process
38. Cloud concepts & application in Data Science
39. Database concepts
40. Statistics fundamentals as needed in Data Science
41. Visualizations for data mining and presentation
42. An overview on Statistical Learning
43. The essentials of Machine Learning
44. More advanced Python to apply to Data Science
45. Understand the basics of probability
46. Be able to implement basic statistics
47. Understand how to use various statistical distributions
48. Apply statistical methods and hypothesis testing to business problems
49. Understand how regression models work
50. Implement one way and two way ANOVA
51. Be able to understand different types of data

★ Disclaimer ★
Developer claims no credit for any video embedded in this app unless otherwise noted. Videos embedded in this app are copyright to its respectful owners. If there is an video appearing in this app that belongs to you and you do not want it to appear in this app, please contact us via email and it will be promptly removed.

★ Icon Credit ★
https://www.flaticon.com/free-icons/data-science