Professional Certificate in Data Engineering

At the end of the Course you will have all the skills to become a Data Engineering Professional.  (The most comprehensive Data Engineering course )

1) Python Programming Basics For Data Science – Python programming plays an important role in the field of Data Science

2) Introduction to Machine Learning – [A –Z] Comprehensive Training with Step by step guidance

3) Setting up the Environment for Machine Learning – Step by step guidance

4) Supervised Learning – (Univariate Linear regression, Multivariate Linear Regression, Logistic regression, Naive Bayes Classifier, Trees, Support Vector Machines, Random Forest)

5) Unsupervised Learning

6) Evaluating the Machine Learning Algorithms

7) Data Pre–processing

8) Algorithm Analysis For Data Scientists

9) Deep Convolutional Generative Adversarial Networks (DCGAN)

10) Java Programming For Data Scientists

We can build a much brighter future where humans are relieved of menial work using AI capabilities.  –  Professor Andrew Ng

Course Learning Outcomes

To provide awareness of Supervised & Unsupervised learning

Describe intelligent problem–solving methods via appropriate usage of Machine Learning techniques.

To build comprehensive neural models from using state–of–the–art python framework.

To build neural models from scratch, following step–by–step instructions. [Step by step guidance with clear explanation]

To build end – to – end comprehensive solutions to resolve real–world problems by using appropriate Machine Learning techniques from a pool of techniques available.