Study Machine Learning Projects with Source Code in Python with Coursera

Machine Learning with Python course by Coursera is for those who want to learn more about procedural programming and Machine Learning (ML) algorithms. It is an extensive certification training. Learners with a bachelor's degree, professionals in their mid-career years, and developers can enroll in this course. 

After the course, one can work as an expert in various settings, including corporations, technology organizations, start-ups, and government bodies. Hands-on rounds and discussion forums are included in the curriculum to provide the best possible learning experience. This course will teach you how to use applied machine learning with Python, a familiar and simple programming language in ML.

The course covers 2 prime components. Primarily, you will learn about machine learning with Python and how it is applied in the real world. The second gives an overview of ML topics such as supervised versus unsupervised learning, model evaluation, and ML algorithms. This course will enable you to apply Machine Learning in real-life situations, and see how it impacts society in myriad ways. If you complete the Machine Learning With Python Coursera course, and earn the Coursera certification, you will be awarded an International Business Machines (IBM) digital badge. 

Saeed Aghabozorgi, Ph.D., Senior Data Scientist at IBM, was my instructor for the course. He possesses a track record for developing enterprise level applications that substantially increases clients’ ability to turn data into actionable knowledge. He is a researcher in the data mining field and expert in developing advanced analytic methods like deep learning, ML and statistical modeling on large datasets. I deeply appreciate his teaching skills.

This online machine learning with python projects certification program is a self-paced, intermediate-level course. It is also aimed at working professionals who would like to expand their skill set. The duration of the course is 21 hours. Some of the critical topics you cover while you undergo this curriculum include Machine Learning, unsupervised learning, supervised learning, clustering, Artificial Intelligence(AI), and more.

The professors who teach this intermediate course are from well-known universities. Thus, the course gives learners a chance to study with international teachers and learn about other cultures. Self-paced discussions are part of the instruction, giving learners the chance to learn online, interact, and learn from different perspectives. The program prepares learners for real-world careers.

Post enrolment, learners are provided access to the study material and given assignments every week. The assignments focus on both the practical and theoretical learning of the learners. The modules of this course are detail-oriented, comprehensive, and practical. Apart from theoretical concepts, the learners also get to learn through hands-on training. 

Technically, the course is spread over 5 prime modules formulated as follows:

Module 1: Introduction to Machine Learning

Module 2: Regression

Module 3: Classification

Module 4: Clustering

Module 5: Recommender Systems

I was in my second year of Bachelors in Technology in Computer Science Engineering (CSE), when I started this course. Machine Learning with Python is a trending subject in technology. I believe equipping myself in this field will help me land a high-profile job in the future.

This machine learning with python certification course is for everyone and elevates learners' skill sets making it simpler for them to advance in their career and even transition to other roles. Because it is a practical program, with a dedicated methodology, it gives learners thorough knowledge.

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