Data Science with Python Career Track

Interested in making a career in the field of Data Science?

Data Science with Python Career Track


Gain the career-transforming skills needed to transition into the field of data science. In this track you'll learn essential mathematics, python programming for data science, 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.

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Job Facts

Popular research states that Data scientists are among the most sought-after positions in America. Yet, many existing and emerging workers don't have the full skillset employers need. A conservative estimate of a data scientist salary is around $113K per annum and could vary based on the experience and skill set. Given the versatility of the field, data scientists are sought to solve problems across various industries ranging from primary sectors such as Marketing, Finance, Banking, Healthcare, Telecom and Insurance to niche sectors such as Automobiles, Education, Sports etc.

What makes this course unique?

This is the first Data Science Career Track with a job guarantee. With support from our career services team, we will help you find a job upon the completion of the course. But if you don’t, we’ll refund your tuition

Who is this course for?

Data Science with Python career track is designed to help an aspirant transition from any background. The only major pre-requisite needed for the course is possessing a growth mindset and nothing else. The career track is designed in such a way that all the requisites are embedded within the curriculum.

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 12 Modules that cover concepts such as essential mathematics, python programming for data science, data science lifecycle, statistical techniques, state of the art machine learning algorithms for supervised and unsupervised learning, recommender systems, artificial intelligence techniques such as neural networks and introduction to deep learning etc.

Skills Gained?

Python Programming

Expertise in Data Visualization, Exploratory Data Analysis etc using NumPy, Pandas, Sklearn etc.

In depth Understanding on core Data Science concepts such as:

1) Statistical Concepts . 2) Supervised and Unsupervised Learning . 3) Neural Networks 4) Introduction to Advanced Deep Learning

Hands on experience via Projects and Assignments

This specialization have 13 courses content

Module 1

Introduction to Data Science

Description: This is an introductory module which is focused towards providing a brief overview on Data Science, Technology trends, Industry Trends, Glossary, Data Science Lifecycle etc.

Skills gained

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  • • What are Analytics and Data Science?

Module 2

Python Programming for Data Science

Description: This module focusses on refreshing basic concepts of python programming and introducing advanced concepts such as OOP, Exception handling, Module building etc.

Skills gained

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  • • Environment Setup and IDE’s in python

Module 3

Unsupervised Learning

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.

Skills gained

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  • • Clustering

Module 4

Text Mining and NLP

Description: this module focusses on extracting meaningful insight from unstructured data such as text

Skills gained

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

Module 5

Introduction to Neural Networks and Deep Learning

Description: Neural networks are a set of algorithms, modeled loosely after the human brain, that are designed to recognize patterns.

Skills gained

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  • • Artificial Neural Networks

Module 6

Math Basics

Description: Provide a brief introduction to essential math before each module.

Skills gained

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  • • Basics of Co-ordinate Geometry

Module 7

Business Statistics

Description: Learn business statistics to better interpret and describe your data.

Skills gained

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  • • Descriptive Statistics – Measures of Centrality and Spread

Module 8

Exploratory Analysis and Data Preprocessing

Description: Data cleansing, wrangling and exploration are critical skills to building an efficient data science solution.

Skills gained

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  • • Types of Datatypes in Data Science

Module 9

Supervised Learning: Regression Techniques

Description: This is the first of two modules on Supervised learning.

Skills gained

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  • • Linear Regression

Module 10

Supervised Learning: Advanced

Description: This is the second of a series of 2 modules on Supervised learning.

Skills gained

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  • • Decision Trees

Module 11

Time series modelling

Description: Get introduced to a popular technique of predicting outcomes as a function of time

Skills gained

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  • • Time Series Forecasting: Solving Forecasting Problems

Module 12

Data Science in Practice

Description: This module focusses on providing resolutions to these challenges

Skills gained

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

Module 13

Data Science Connector

Description: This is a connector module that encompasses concepts that are required to bridge various modules.

Skills gained

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  • • Data Science Lifecycle in detail

Why Us?

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We also provide features like :-
  • Lifetime content access to the LMS
  • 24/7 coding support
  • Placement assistance
  • Live projects

Limited students per batch !!

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