IMTalent | Data Science Using Python

Overview

Rapid technological advances in Data Science have been reshaping global businesses and putting performances on overdrive. As yet, companies are able to capture only a fraction of the potential locked in data, and data scientists who are able to reimagine business models by working with Python are in great demand.

Python is one of the most popular programming languages for high level data processing, due to its simple syntax, easy readability, and easy comprehension. Python’s learning curve is low, and due to its many data structures, classes, nested functions and iterators, besides the extensive libraries, this language is the first choice of data scientists for analysing, extracting information and making informed business decisions through big data.

This Data science for Python programming course is an umbrella course covering major Data Science concepts like exploratory data analysis, statistics fundamentals, hypothesis testing, regression classification modeling techniques and machine learning algorithms.

Extensive hands-on labs and an interview prep will help you land lucrative jobs.

Learning Outcome

Data Science Tools & Technologies
- Get acquainted with various analysis and visualization tools such as matplotlib and seaborn
Statistics for Data Science
- Understand the behavior of data as you build significant models and gain strong concepts on Statistics Fundamentals
Python for Data Science
- Learn about the various libraries offered by Python to manipulate data. Use of various Python libraries like Numpy, Pandas, Scikit-Learn, Statsmodel
Exploratory Data Analysis
- Use Python libraries and work on data manipulation, data preparation and data explorations
Data Visualization using Python
- Use of Python graphics libraries like Matplotlib, Seaborn etc.
Advanced Statistics & Predictive Modeling
- Learn about Analysis of Variance and its practical uses
- Learn to apply Linear Regression with OLS Estimate to predict a continuous variable
- Learn to apply Binomial Logistic Regression for Binomial Classification Problems

Who should Attend?

This course is for you if:

You are interested in the field of data science and want to learn essential data science skills
You are new to Python or are self-taught and you are looking for a more robust, structured learning program
You're a Data Analyst, Economist, or Researcher who works with large datasets and wants to make analysis easier and more effective with Python
You're a Software or Data Engineer interested in learning the fundamentals of quantitative analysis

Eligibility Criteria

There are no prerequisites to attend this course, but elementary programming knowledge will come in handy.

This course is endorsed under Critical Infocomm Technology Resource Programme Plus (CITREP+) Programme.
To find out more about CITREP+ Funding, please refer to Programme Support under CITREP+ page

Information is accurate as of 31July 2020