If youâre plugged into the tech industry, youâll know that two things have been making consistent waves in many areas over the past few years; machine learning and Python. What happens when you combine the new gold standard programming language with the most significant tech development in areas such as financial trading, online search, digital marketing and even data and personal security (among others)? Great things, thatâs what. This course will show you whatâs what, and get you started on becoming a machine learning guru.Increase Your Python ExpertiseIf you have a desire to learn machine learning concepts and have some previous programming or Python experience, this course is perfect for you. If youâre more of a beginner than an intermediate, donât worry; each module starts with theory to explain upcoming concepts. Once youâre comfortable, youâll put your knowledge into practice with a code walk through.The goal of this course is to build procedural machine learning from the ground up. Writing processing from scratch allows students to gain a more in-depth insight into data processing, and as each machine learning app is created, explanations and comments are provided to help students understand why things are being done in certain ways. Each code walk through also shows the building process in real time.The course begins with an introduction to machine learning concepts, after which youâll build your first machine learning application. Following that, we look at data analysis, linear algebra, natural language processing and clustering, all within the context of Python. At the end of the course, youâll be issued with a certificate of completion and will have gained a full introduction into the world of machine learning with Python.What is Machine Learning?Machine learning is a method of data analysis that essentially allows computers to âlearnâ on their own without being explicitly programmed. For example, when you stop scrolling through Facebook to read a friend or a pageâs post, algorithms automatically work to make sure youâll see more content from those sources earlier in your news feed in future.