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Self Paced

Python for Data Science

Master Python for Data Science: From Basics to Data-Driven Insights

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Enroll now for early access of e-LMS

MODE
Online/ e-LMS

TYPE
Self Paced

LEVEL
Moderate

DURATION
1 hours

About

This one-hour program introduces the fundamentals of Python, emphasizing its applications in data science. Participants will learn to use Python for data manipulation, performing basic data analysis, creating visualizations, and understanding basic machine learning concepts.

Aim

To provide learners with foundational skills in Python programming, focusing on data analysis, visualization, and introductory machine learning concepts. This course aims to equip participants with essential tools to manipulate, analyze, and visualize data efficiently using Python.

Program Objectives

Gain a strong foundation in Python programming.
Learn to manipulate and analyze data using Python libraries.
Create effective data visualizations.
Understand basic machine learning concepts.
Apply Python skills to real-world data science problems.

Program Structure

Module 1: Python Basics
1. Introduction to Python
  - Understanding Python’s role in data science
  - Setting up Python environment (Anaconda, Jupyter Notebook)
  - Basic syntax, variables, and data types
2. Control Structures
  - If-else statements
  - For and while loops
  - List comprehensions
3. Functions and Modules
  - Defining functions
  - Importing and using libraries (NumPy, Pandas, Matplotlib)
  - Writing and organizing Python scripts
4. Basic Data Structures
  - Lists, tuples, dictionaries, and sets
  - Manipulating and accessing data structures
Module 2: Data Manipulation with Pandas
1. Introduction to Pandas
  - Understanding DataFrames and Series
  - Loading data from CSV, Excel, and other file formats
2. Data Cleaning and Preprocessing
  - Handling missing data
  - Filtering, sorting, and grouping data
  - Applying functions across data
3. Data Transformation
  - Merging, joining, and concatenating DataFrames
  - Pivot tables and cross-tabulation
  - Data aggregation and summarization
Module 3: Data Visualization with Matplotlib
1. Introduction to Data Visualization
  - Importance of visualization in data science
  - Overview of Matplotlib and Seaborn
2. Creating Basic Plots
  - Line plots, bar charts, and histograms
  - Customizing plots: labels, titles, and legends
3. Advanced Visualization Techniques
  - Scatter plots, box plots, and heatmaps
  - Multiple plots and subplots
  - Saving and exporting visualizations

Participant’s Eligibility

Beginners in programming, data analysts, researchers, and students in data science.

Program Outcomes

Proficiency in Python for data analysis and visualization.
Ability to manipulate and analyze datasets using Python.
Basic understanding of machine learning concepts.
Capability to create data visualizations and interpret them.
Hands-on experience with Python tools in data science.

Fee Structure

Standard Fee: INR ~~1,000~~ USD 40

Discounted Fee: INR 500 USD 20

We are excited to announce that we now accept payments in over 20 global currencies, in addition to USD. Check out our list to see if your preferred currency is supported. Enjoy the convenience and flexibility of paying in your local currency!

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Certificate

Program Assessment

Certification to this program will be based on the evaluation of following assignment (s)/ examinations:

Exam	Weightage
Mid Term Assignments	50 %
Project Report Submission (Includes Mandatory Paper Publication)	50 %

To study the printed/online course material, submit and clear, the mid term assignments, project work/research study (in completion of project work/research study, a final report must be submitted) and the online examination, you are allotted a 1-month period. You will be awarded a certificate, only after successful completion/ and clearance of all the aforesaid assignment(s) and examinations.

Program Deliverables

Access to e-LMS
Real Time Project for Dissertation
Project Guidance
Paper Publication Opportunity
Self Assessment
Final Examination
e-Certification
e-Marksheet

Future Career Prospects

Data Analyst
Data Scientist
Machine Learning Engineer
Python Developer
Business Analyst
Research Scientist

Job Opportunities

Data science roles in tech companies
Analytics departments in finance and healthcare
Research positions in academic institutions
Startups focusing on data-driven solutions
Government agencies dealing with data
Consulting firms specializing in data analysis

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