Machine Learning Engineer Pathway

Machine Learning skills are some of the most sought-after in the modern job market. Modern ML Engineers make dozens of thousands of dollars more per year than other developers. This path will teach you the essential ML techniques to stand out from the competition. By the end, you'll have job-ready skills in data pipeline creation, model deployment, and inference.

Freshers (20).png

Learning Objectives

Learn to analyze and manipulate data in Pandas and Numpy.

Understand the basics of image recognition using variations of Convolutional neural networks (CNN).

Gain a mastery of multithreading and concurrency concepts in C++

Dive into Deep Learning with TensorFlow and Keras.

Get the hang of Natural Language Processing and related concepts.

Learn to design ML-based systems such as search ranking, recommender systems, and others.

Hands-On Programs

Machine Learning for Software Engineers

Explore the basics of machine learning with data analysis and algorithm selection through job-focused lessons and hands-on practice.

Natural Language Processing with Machine Learning

Master the NLP techniques essential for text-to-speech and semantic analysis technology.

Applied Machine Learning: Industry Case Study with TensorFlow

Image Recognition with Machine Learning

Learn to create the algorithms behind innovations like computer vision and self-driving cars.

Applied Machine Learning: Deep Learning for Industry

Apply previous modeling and data pipeline concepts to create industry-ready Deep Learning projects.

Combine what you've learned so far to analyze a real-world case from start to finish.