logo

Core Data Science Career Track

Are you an inquisitive mind and does conveying stories from numbers excite you? Sign up to our 4-month Instructor-led Core Data Science career track

Are you an inquisitive mind and does conveying stories from numbers excite you? Sign up to our 4-month Instructor-led Core Data Science career track

Overview

+

Gain the career-transforming skills needed to transition into the field of data science. In this track, you'll learn everything that one needs to learn about data science like data science lifecycle, statistical techniques, state of the art machine learning algorithms for supervised and unsupervised learning, artificial intelligence techniques such as deep learning, etc., real-world applications of these techniques via challenging case studies to solve business problems. This track is focused on building depth in core data science and will prepare an aspirant for taking up challenging data science roles. A pre-requisite to sign up for this course is some prior experience with python programming and pydata stack.

What you will learn

The primary motive of this track is to equip a Data Science aspirant with all the necessary skills to crack any Data Science interview. The focus will be on building a strong foundation for any specializations. The career track has 10 Modules that cover concepts such as data science lifecycle, statistical techniques, state of the art machine learning algorithms for supervised and unsupervised learning, artificial intelligence techniques such as deep learning etc., real world applications of these techniques via challenging case studies to solve business problems

Skills Gained?

In depth Understanding on core Data Science concepts such as: Statistical Concepts, Supervised, Unsupervised Learning, Neural Networks , and Introduction to Advanced Deep Learning

Hands on experience via Projects and Assignments

This specialization have 10 courses content

Description: Learn business statistics to better interpret and describe your data. This module spans from simple descriptive statistics to advanced inferential statistics. Statistics forms the foundation for any data science learning track and gathering this knowledge in an application-oriented manner would greatly help.

Skills gained

+
  •  

    • Descriptive Statistics – Measures of Centrality and Spread
Description: Data cleansing, wrangling and exploration are critical skills to building an efficient data science solution. Learn techniques to cleanse, preprocess and explore data using Pythons visualization libraries such as Matplotlib and Seaborn

Skills gained

+
    • Types of Datatypes in Data Science

Description: This is the first of two modules on Supervised learning. Get introduced to statistical regression techniques such as Linear, Logistic regression and advanced approaches to improve models

Skills gained

+
    • Linear Regression

Description: This is the second of a series of 2 modules on Supervised learning. This module introduces advanced ML algorithms such as tree-based models, ensemble learning and support vector machines.

Skills gained

+
    • Decision Trees

Description: Unsupervised learning unlike its counterpart, is a type of machine learning that looks for previously undetected patterns in a data set with no pre-existing labels. A deep dive into state-of-the-art unsupervised learning techniques such as clustering, recommender systems etc.

Skills gained

+
    • Clustering

      • K Means Clustering

      • Hierarchical Clustering

      • DBSCAN

Description: Get introduced to a popular technique of predicting outcomes as a function of time. The module starts with simple forecasting techniques and progresses into complex techniques such as Auto regression etc.

Skills gained

+
    • Time Series Forecasting: Solving Forecasting Problems

Description: While until this point in the course we have been majorly working with structured data, this module focusses on extracting meaningful insight from unstructured data such as text.

Skills gained

+
    • Text Preprocessing – Stemming, Lemmatization, Word Clouds etc.

Description: Neural networks are a set of algorithms, modeled loosely after the human brain, that are designed to recognize patterns. Learn the philosophy behind Neural Networks and how they extract complex patterns. Introduce yourself to how these can be applied for various types of data, structured and unstructured.

Skills gained

+
    • Artificial Neural Networks

Description: While all the above techniques are great and yield amazing results, implementing these algorithms in real-world could be very challenging due to various constraints such as volume of data, operationalization, etc. This module focusses on providing resolutions to these challenges

Skills gained

+
    • Discussion on typical challenges faced while operationalizing data science solutions.

Description: This is a connector module that encompasses concepts that are required to bridge various modules. This module is responsible for ensuring that the aspirant has the necessary information before moving into another module. This module spans throughout the course.

Skills gained

+
    • Data Science Lifecycle in detail


What will you learn?


The primary motive of this track is to equip a Data Science aspirant with all the necessary skills to crack any Data Science interview. The focus will be on building a strong foundation for any specializations. The career track has 10 Modules that cover concepts such as data science lifecycle, statistical techniques, state of the art machine learning algorithms for supervised and unsupervised learning, artificial intelligence techniques such as deep learning etc., real world applications of these techniques via challenging case studies to solve business problems

Frequently asked questions

Hire from us/contact us

If you have question or would like more information on our works, Please complete the form and we'll aim get back to you in 24 hours.

Why Us

Lorem Ipsum is simply dummy text of the printing and typesetting industry. Lorem Ipsum has been the industry's standard dummy text ever since the 1500s, when an unknown printer took a galley of type and scrambled it to make a type specimen book. It has survived not only five centuries, but also the leap into electronic typesetting, remaining essentially unchanged. It was popularised in the 1960s with the release of Letraset sheets containing Lorem Ipsum passages, and more recently with desktop publishing software like Aldus PageMaker including versions of Lorem Ipsum.