Data Science using Python

Data Science using Python

Data Science using Python will introduce the learner to the python programming environment, including fundamental python programming techniques such as lambdas, reading and manipulating csv files, NumPy library, concepts of Supervised and Unsupervised learning, Forecasting Techniques and Integration with Spark.

Total Lessons

15 Lessons

Program Duration

5 Weeks Only

Learning Format

Data Science using Python

Course Overview

Sale!

Data Science using Python

1,999.009,999.00

The Data Science with Python course helps to introduce data manipulation and cleaning techniques using the popular python panda’s data science library and introduce the abstraction of the Series and Data Frame as the central data structures for data analysis, along with tutorials on how to use functions such as groupby, merge, and pivot tables effectively.

By the end of this course, students will be able to take tabular data, clean it, manipulate it, and run basic inferential statistical analysis.

Offline Course
(Self-Paced)

  • 35 hrs of self-learning
  • 4-months of LMS Access
  • 35 hrs of self-driven exercises/quiz

Online Course
(Trainer Driven Virtual Sessions)

  • Live sessions of 35 hrs
  • 35 hrs of guided exercises/quiz
  • Guided Project and Viva presentation
  • 4-months of LMS Access
Clear

Description

Gain new insights into your data. Learn to apply data science methods and techniques and acquire analysis skills.

Additional information

Classes

Offline Course, Online Course

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Key Highlights


Online Courses


  • Access to Question Bank/Exams
  • LMS Access for 4 months post enrolment
  • Access to Lagozon Technology Team
  • Training/Internship Certificates
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Offline Courses


  • Access to Question Bank/Exams
  • LMS Access for 4 months post enrolment
  • Course completion certificate

Course Curriculum

  • Introduction to Data Science
  • Python Basic Constructs
  • Maths for DS-Statistics & Probability
  • Numpy for Mathematical Computing
  • Scipy for Scientific Computing
  • Data Manipulation
  • Data visualization with Matplotlib
  • Machine Learning with Python
  • Supervised learning
  • Unsupervised Learning
  • Data Science Concepts
  • Python Integration with Spark
  • Dimensionality Reduction
  • Time Series Forecasting
  • Industry Relevant Project

Skills Covered

Machine Learning

Data Manipulation

Time Series Forecasting

Dimensionality Reduction

Python functionality used for data science

Distributions, sampling, and t-tests

Query Data Frame structures

Who can apply?

  • Anyone who is passionate to learn and enhance skills in data analytics
  • IT/ Non-IT Professionals
  • College Graduates
  • BI Professionals
  • Project Managers
  • MBA and BBA Students from all specializations
  • BCA/MCA