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VERSION:2.0
PRODID:-//KnowAFest//Campus Events//EN
BEGIN:VEVENT
UID:eventsphere-63913@www.knowafest.com
DTSTAMP:20261008T164320Z
DTSTART:20250822T183000Z
DTEND:20250823T182959Z
SUMMARY:Python for Data Science Workshop 2025
LOCATION:Top Engineers\, Chennai
DESCRIPTION:<p>Session 1: Python Basics &amp\; Setup<br />\nObjective: Get 
 comfortable with Python syntax\, working in Jupyter Notebook\, and basic<b
 r />\nprogramming concepts.<br />\nIntroduction to Python for Data Science
 <br />\nSetting Up the Environment: Installing Anaconda\, Jupyter Notebook
  basics<br />\nPython Data Types &amp\; Variables: Integers\, Floats\, Str
 ings\, Lists\, Tuples\, Dictionaries<br />\nOperators &amp\; Control Flow:
  Conditional statements (if-else)\, Loops (for\, while)<br />\nFunctions &
 amp\; Lambda Functions: Writing reusable functions for data processing<br 
 />\nHands-on Exercises: ✅ Writing basic Python scripts<br />\n✅ Using 
 loops and conditions<br />\n✅ Creating simple functions<br />\nSession 2
 : Working with NumPy<br />\nObjective: Learn to manipulate numerical data 
 efficiently using NumPy arrays.<br />\nIntroduction to NumPy<br />\nCreati
 ng NumPy Arrays: array()\, zeros()\, ones()\, arange()\, linspace()<br />\
 nIndexing &amp\; Slicing: Accessing elements\, slicing subarrays<br />\nMa
 thematical &amp\; Statistical Operations: sum()\, mean()\, std()\, var()<b
 r />\nBroadcasting &amp\; Vectorized Operations: Applying operations on en
 tire arrays efficiently<br />\nHands-on Exercises: ✅ Creating and manipu
 lating arrays<br />\n✅ Performing mathematical computations on datasets<
 br />\nSession 3: Data Analysis with Pandas<br />\nObjective: Understand h
 ow to manipulate tabular data using Pandas.<br />\nIntroduction to Pandas<
 br />\nCreating &amp\; Loading DataFrames: pd.DataFrame()\, read_csv()\, r
 ead_excel()<br />\nExploring Data: head()\, info()\, describe()\, shape\, 
 columns●<br />\nData Cleaning &amp\; Preprocessing: Handling missing val
 ues (dropna()\, fillna())\,<br />\nchanging data types<br />\nFiltering &a
 mp\; Sorting Data: query()\, sort_values()\, groupby()\, apply()<br />\nMe
 rging &amp\; Concatenating DataFrames: merge()\, concat()<br />\nHands-on 
 Exercises: ✅ Loading a dataset and exploring it<br />\n✅ Cleaning miss
 ing values and transforming data<br />\nBreak (15 mins)<br />\nA short bre
 ak to refresh.<br />\nSession 4: Data Visualization with Matplotlib &amp\;
  Seaborn<br />\nObjective: Learn to visualize data and extract insights.<b
 r />\nIntroduction to Data Visualization<br />\nMatplotlib Basics: plot()\
 , scatter()\, bar()\, hist()<br />\nSeaborn for Statistical Graphics: boxp
 lot()\, pairplot()\, heatmap()<br />\nCustomizing Plots: Titles\, labels\,
  legends\, figure sizes<br />\nHands-on Exercises: ✅ Creating various pl
 ots for a dataset<br />\n✅ Customizing visualizations<br />\nSession 5: 
 Hands-on Data Science Project<br />\nObjective: Apply everything learned t
 o analyze a real-world dataset.<br />\nDataset Selection: Working with a d
 ataset (e.g.\, Titanic\, COVID-19\, Sales data)<br />\nData Cleaning: Hand
 ling missing values\, feature selection<br />\nExploratory Data Analysis (
 EDA): Summary statistics\, correlations<br />\nData Visualization: Creatin
 g meaningful charts to derive insights<br />\nHands-on Activities: ✅ Per
 form data cleaning<br />\n✅ Generate visualizations and report insights<
 br />\n<br />\n<br />\n**NOTE: LAPTOP IS MANDATORY\, SINCE HANDS-ON SESSIO
 NS NEEDS PROGRAMMING</p>
URL:https://www.knowafest.com/python-for-data-science-workshop-2025-top-eng
 ineers
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