woosquare domain was triggered too early. This is usually an indicator for some code in the plugin or theme running too early. Translations should be loaded at the init action or later. Please see Debugging in WordPress for more information. (This message was added in version 6.7.0.) in /home2/magnimin/public_html/magnimind_academy/wp-includes/functions.php on line 6114wpforms domain was triggered too early. This is usually an indicator for some code in the plugin or theme running too early. Translations should be loaded at the init action or later. Please see Debugging in WordPress for more information. (This message was added in version 6.7.0.) in /home2/magnimin/public_html/magnimind_academy/wp-includes/functions.php on line 6114wordpress-seo domain was triggered too early. This is usually an indicator for some code in the plugin or theme running too early. Translations should be loaded at the init action or later. Please see Debugging in WordPress for more information. (This message was added in version 6.7.0.) in /home2/magnimin/public_html/magnimind_academy/wp-includes/functions.php on line 6114Whether you come from the IT or design field with a bit of coding experience, or a completely unrelated field, a curriculum like the following can help to your data science learning path<\/strong>:<\/p>\n Apart from knowing what data science is, you will have tutorials from Python Foundations and Apache Spark<\/strong> from scratch. Then you will be taught how to get started with Apache Spark on Databricks<\/strong>.<\/p>\n From explanatory data analysis, and statistics with Python to Spark APIs (both structured and unstructured), data extraction, and the importance of Spark architecture for big data and more, you will get to know a lot of things about data science.<\/p>\n Your lessons will start with linear regression and logistic regression, and then proceed to understanding evaluating models in data science and interpreting them. You will also learn how to choose the right model best suited for the task at hand. This week is likely to include some more lessons on Spark such as exploring and preprocessing\u00a0the\u00a0data with Spark, ways to do feature extraction using Spark etc.<\/p>\n You will delve deeper into machine learning this week to learn about support vector machines<\/strong>, as well as random forest and decision trees. You will also learn about using decision trees and linear regression with Spark<\/strong><\/a>.<\/p>\n From an introduction to clustering and the top clustering algorithms you need to know, to clustering with Spark<\/strong>, this week will keep you busy by teaching you the unsupervised machine learning technique. This week will also let you learn about dimension reduction or variable reduction techniques along with Principal Component Analysis (PCA)<\/strong>.<\/p>\n An intensive learning course in data science wouldn\u2019t be complete without real-life projects. That\u2019s exactly what you get to do during the last week after learning feature evaluation and cross validation, as well as hyper parameter optimization and tuning.<\/p>\n So, get started on your data science career by taking a 6-week course like the one above that will get you job-ready.<\/p>\nWeek 1: Data science fundamentals<\/strong><\/h5>\n
Week 2:<\/strong> Explanatory Analysis <\/strong><\/h5>\n
Week 3:<\/strong> Machine Learning-I<\/strong><\/h5>\n
Week 4: Machine Learning-II<\/strong><\/h5>\n
Week 5: Machine Learning-III<\/strong><\/h5>\n
Week 6: Projects<\/strong><\/h5>\n