Get upskilled in Data Science

Our data science training programs are meticulously designed to cover adequate technical details and real world use cases to propel your data science career. Whether you are a beginner who wants to jumpstart your data science career or a data science executive looking to advance further, we have something for you.

Our Upskilling Courses

Course Summary: Introduce participants to python programming language, which is a most popular language for data science and analytics. This is an introductary course that equips participants with programming the Pythonic way and how to do basic data wrangling and manipulation.

Target level: Beginner

Duration: 5 days

Pre-requisite: Basic Programming Knowledge

Course Contents:

  • Overview of Python Programming

  • Control Structures and Arrays

  • Manipulating Data with Pandas

  • Data Visualization with Python

  • Guided Tutorials & Laboratory Exercises

Course Summary: Introduce participants to machine learning with Python, focusing more on the techniques and methods than the statistics behind these methods. Participants will be introduced to various algorithms and how to apply them on real datasets with the help of scikit learn toolkit.

Target level: Beginner

Duration: 5 days

Pre-requisite: Basic Python Programming Knowledge

Course Contents:

  • Introduction to Machine Learning

  • Supervised Learning Algorithms & Applications

  • Parameter Tuning & Regularization

  • Unsupervised Learning Algorithms & Applications

  • Ensemble Methods to Improve Performance

  • Neural Networks and Deep Learning

Course Summary: The popularity of Deep Learning has skyrocketed over the past few years. This course aim to expose aspiring "deep learners" to using deep learning to approach state-of-the-art problems in speech recognition, object detection, and many other tasks that humans normally excel in, using Google's open-sourced platform, Tensorflow.

Target level: Intermediate

Duration: 5 days

Pre-requisite: Python, Machine Learning

Course Contents:

  • Introduction to Deep Learning (DL)

  • Optimization & Regularization

  • Convolutional Neural Networks for Images

  • Recurrent Neural Networks for Texts

  • Deploying DNN to Production

  • DL Use Cases & Best Practices

Track Records

Our tailored courses have benefitted multiple reputable companies

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