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  • Python, an open-sourced, high-level language crucial for data scientists, offers exceptional performance in mathematics and statistics. Aspiring data scientists can gain comprehensive insights from our industry-experienced trainers, ensuring proficiency for real-world applications. This dynamic training, including interactive discussions and a 100% placement guarantee, positions you for success in the evolving field of data science. Elevate your skills with us, where Python meets the challenges of real-world data.
    • Comprehensive Python and mathematics training

      Industry-experienced trainers

      Interactive group discussions and debates

      100% placement guarantee

  • Embark on a learning expedition where Python mastery aligns seamlessly with the demands of the data science landscape, setting you on a path to success. Elevate your skills and navigate the dynamic challenges of the data-driven world with confidence.

Python for Data Science Training in Chennai

About-Us-Course

  • Enroll in our dynamic Python for Data Science in Chennai where our courses are meticulously crafted to align with the latest features, specifications, and industry trends. Explore the world of Python with ample opportunities to learn and grow.
    • From Scratch to Mastery: Our experienced trainers take you through the fundamentals, starting with expressions and variables. Gain a deep understanding of essential data structures like lists, tuples, dictionaries, and sets.

      Beyond Basics: Move beyond the basics as our trainers delve into the utilization and implementation of advanced concepts such as loops, functions, objects, and classes.

      Hands-On Data Manipulation: Work seamlessly with data using Pandas and NumPy libraries. Acquire practical skills that bridge the gap between theory and real-world application.

      Comprehensive Learning: This training doesn't just provide theoretical knowledge but also offers hands-on practical experience.

      Study Materials: As part of our commitment to your learning journey, we provide study materials that complement the course content, ensuring you have the resources you need.

  • Master Python for Data Science with us, gaining the expertise needed to thrive in the ever-evolving landscape of data-driven technologies. Enroll today and elevate your skills.

  • Furthermore, embarking on our online certification journey will provide you access to exclusive insights about this course. You'll not only gain a foundational understanding but also uncover hidden nuances right from the beginning.
  • Possessing this legitimate accreditation opens the door for a sustained commitment to the course. Our trainers are dedicated to assisting you in securing a position in a specific company.
  • To be precise, acquiring in-depth knowledge through this certification can potentially lead to annual earnings of around 10.2 lakhs INR. Your investment in learning pays off both in knowledge and tangible career benefits.

  • Entering the field of Data Science presents a compelling opportunity due to the high demand for professionals. Choosing this path not only exposes you to the intricacies of the field but also positions you to excel and reach the pinnacle of your career.
  • Acquiring a legitimate certification significantly enhances your chances of securing a position within an organization. Moreover, immersing yourself in the specific knowledge of the field propels you toward becoming a proficient professional.
  • As a freelancer, you can also achieve substantial financial success. The versatility of your skills opens doors to opportunities in multinational companies. Obtaining this accreditation not only validates your skills but also enables you to work professionally as a recognized Data Scientist. Seize the chance to thrive in this dynamic and lucrative field.

  • Opting for this certification offers several compelling reasons. One of the key factors is the substantial demand, promising scope, and widespread applicability across various sectors. If your goal is to become a successful Data Scientist, obtaining this accreditation is undoubtedly a wise choice.
  • Your mathematical and statistical skills will undergo refinement, adding depth to your expertise. Furthermore, your programming skills will experience enhancement, making you a proficient Data Scientist. The certification ensures a comprehensive understanding of the intricate details of the field.
  • Beyond skill development, this accreditation opens doors to opportunities with major establishments such as TCS, IBM, and more, providing a pathway to a successful and impactful career in Data Science.

  • the role of a Data Scientist encompasses a diverse range of responsibilities, with a primary focus on managing substantial volumes of data. Understanding the tasks involved is crucial once you step into the shoes of a Data Scientist.
  • Your primary responsibility will involve utilizing raw data to extract valuable insights. Additionally, you'll be tasked with interpreting large datasets and contributing to business-driven decisions through comprehensive data analysis. Automation of data collection and management processes will also fall under your purview.
  • In essence, you'll be actively involved in the processing and cleansing of data as part of your job role. The multifaceted nature of a Data Scientist's responsibilities underscores the dynamic and impactful nature of the role.

  • Explore opportunities with leading organizations actively seeking Data Scientists, including IBM, TCS, Accenture, Wipro, Amazon, and Cognizant.
  • Choosing this specialized field promises multiple benefits. With this accreditation, expect an upward trajectory in your career, securing a highly competitive position and enjoying an augmented salary package. Elevate your professional journey by aligning with the top players in the industry.

  • Enrolling in Croma Campus opens doors to a diverse array of certifications spanning various industries, widely recognized within the IT domain.
  • Acquiring accreditation from Croma Campus enhances your prospects of securing a position in a reputable workspace. Our interactive training approach not only imparts knowledge but also refines your communication skills.
  • Gain access to the Learning Management System, offering a comprehensive overview of your performance, class videos, assignments, and more. Croma Campus ensures a holistic learning experience to empower your professional growth.

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Course Duration 40-45 Days 7 Weekends 8 Days
Hours 1 Hrs. Per Day 2 Hrs. Per Day 6+ Hrs. Per Day
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CURRICULUM & PROJECTS

Python for Data Scientist Training

  • Python has been a favourite option for Data Scientists who use it for building and using Machine Learning Applications and other Scientific Computations. Python cuts development time in half with its simple to read syntax and easy compilation feature. Debugging programs is a breeze in Python with its built in debugger.
  • In this program you will learn:
    • Python Training

      Data Analysis and Visualization using Pandas.

      Data Analysis and Visualization using NumPy and MatPlotLib

      Introduction to Data Visualization with Seaborn

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  • Introduction To Python
    • Installation and Working with Python

      Understanding Python variables

      Python basic Operators

      Understanding the Python blocks.

  • Python Keyword and Identiers
    • Python Keyword and Identiers

      Python Comments, Multiline Comments.

      Python Indentation

      Understating the concepts of Operators

      • Arithmetic
      • Relational
      • Logical
      • Assignment
      • Membership
      • Identity
  • Introduction To Variables
    • Variables, expression condition and function

      Global and Local Variables in Python

      Packing and Unpacking Arguments

      Type Casting in Python

      Byte objects vs. string in Python

      Variable Scope

  • Python Data Type
    • Declaring and using Numeric data types

      Using string data type and string operations

      Understanding Non-numeric data types

      Understanding the concept of Casting and Boolean.

      Strings

      List

      Tuples

      Dictionary

      Sets

  • Control Structure & Flow
    • Statements – if, else, elif

      How to use nested IF and Else in Python

      Loops

      Loops and Control Statements.

      Jumping Statements – Break, Continue, pass

      Looping techniques in Python

      How to use Range function in Loop

      Programs for printing Patterns in Python

      How to use if and else with Loop

      Use of Switch Function in Loop

      Elegant way of Python Iteration

      Generator in Python

      How to use nested Loop in Python

      Use If and Else in for and While Loop

      Examples of Looping with Break and Continue Statement

      How to use IN or NOT IN keyword in Python Loop.

  • Python Function, Modules and Packages
    • Python Syntax

      Function Call

      Return Statement

      Arguments in a function – Required, Default, Positional, Variable-length

      Write an Empty Function in Python –pass statement.

      Lamda/ Anonymous Function

      *args and **kwargs

      Help function in Python

      Scope and Life Time of Variable in Python Function

      Nested Loop in Python Function

      Recursive Function and Its Advantage and Disadvantage

      Organizing python codes using functions

      Organizing python projects into modules

      Importing own module as well as external modules

      Understanding Packages

      Random functions in python

      Programming using functions, modules & external packages

      Map, Filter and Reduce function with Lambda Function

      More example of Python Function

  • Python Date Time and Calendar
    • Day, Month, Year, Today, Weekday

      IsoWeek day

      Date Time

      Time, Hour, Minute, Sec, Microsec

      Time Delta and UTC

      StrfTime, Now

      Time stamp and Date Format

      Month Calendar

      Itermonthdates

      Lots of Example on Python Calendar

      Create 12-month Calendar

      Strftime

      Strptime

      Format Code list of Data, Time and Cal

      Locale’s appropriate date and time

  • List
    • What is List.

      List Creation

      List Length

      List Append

      List Insert

      List Remove

      List Append & Extend using “+” and Keyword

      List Delete

      List related Keyword in Python

      List Revers

      List Sorting

      List having Multiple Reference

      String Split to create a List

      List Indexing

      List Slicing

      List count and Looping

      List Comprehension and Nested Comprehension

  • Tuple
    • What is Tuple

      Tuple Creation

      Accessing Elements in Tuple

      Changing a Tuple

      Tuple Deletion

      Tuple Count

      Tuple Index

      Tuple Membership

      TupleBuilt in Function (Length, Sort)

  • Dictionary
    • Dict Creation

      Dict Access (Accessing Dict Values)

      Dict Get Method

      Dict Add or Modify Elements

      Dict Copy

      Dict From Keys.

      Dict Items

      Dict Keys (Updating, Removing and Iterating)

      Dict Values

      Dict Comprehension

      Default Dictionaries

      Ordered Dictionaries

      Looping Dictionaries

      Dict useful methods (Pop, Pop Item, Str , Update etc.)

  • Sets
    • What is Set

      Set Creation

      Add element to a Set

      Remove elements from a Set

      PythonSet Operations

      Frozen Sets

  • Strings
    • What is Set

      Set Creation

      Add element to a Set

      Remove elements from a Set

      PythonSet Operations

  • Python Exception Handling
    • Python Errors and Built-in-Exceptions

      Exception handing Try, Except and Finally

      Catching Exceptions in Python

      Catching Specic Exception in Python

      Raising Exception

      Try and Finally

  • Python File Handling
    • Opening a File

      Python File Modes

      Closing File

      Writing to a File

      Reading from a File

      Renaming and Deleting Files in Python

      Python Directory and File Management

      List Directories and Files

      Making New Directory

      Changing Directory

  • Python Database Interaction
    • SQL Database connection using

      Creating and searching tables

      Reading and Storing cong information on database

      Programming using database connections

  • Contacting user Through Emails Using Python
    • Installing SMTP Python Module

      Sending Email

      Reading from le and sending emails to all users

  • Reading an excel
    • Working With Excel

      Reading an excel le using Python

      Writing to an excel sheet using Python

      Python| Reading an excel le

      Python | Writing an excel le

      Adjusting Rows and Column using Python

      ArithmeticOperation in Excel le.

      Play with Workbook, Sheets and Cells in Excel using Python

      Creating and Removing Sheets

      Formatting the Excel File Data

      More example of Python Function

  • Complete Understanding of OS Module of Python
    • Check Dirs. (exist or not)

      How to split path and extension

      How to get user prole detail

      Get the path of Desktop, Documents, Downloads etc.

      Handle the File System Organization using OS

      How to get any les and folder’s details using OS

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  • Statistics
    • Categorical Data

      Numerical Data

      Mean

      Median

      Mode

      Outliers

      Range

      Interquartile range

      Correlation

      Standard Deviation

      Variance

      Box plot

  • Pandas
    • Read data from Excel File using Pandas More Plotting, Date Time Indexing and writing to les

      How to get record specic records Using Pandas Adding & Resetting Columns, Mapping with function

      Using the Excel File class to read multiple sheets More Mapping, Filling

      Nonvalue’s

      Exploring the Data Plotting, Correlations, and Histograms

      Getting statistical information about the data Analysis Concepts, Handle the None Values

      Reading les with no header and skipping records Cumulative Sums and Value Counts, Ranking etc

      Reading a subset of columns Data Maintenance, Adding/Removing Cols and Rows

      Applying formulas on the columns Basic Grouping, Concepts of Aggre

      gate Function

      Complete Understanding of Pivot Table Data Slicing using iLoc and Loc property (Setting Indices)

      Under sting the Properties of Pivot Table in Pandas Advanced Reading

      CSVs/HTML, Binning, Categorical Data

      Exporting the results to Excel Joins:

      Python | Pandas Data Frame Inner Join

      Under sting the properties of Data Frame Left Join (Left Outer Join)

      Indexing and Selecting Data with Pandas Right Join (Right Outer Join)

      Pandas | Merging, Joining and Concatenating Full Join (Full Outer Join)

      Pandas | Find Missing Data and Fill and Drop NA Appending DataFrame and Data

      Pandas | How to Group Data How to apply Lambda / Function on Data

      Frame

      Other Very Useful concepts of Pandas in Python Data Time Property in Pandas (More and More)

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  • NumPy
    • Introduction to NumPy: Numerical Python

      Importing NumPy and Its Properties

      NumPy Arrays

      Creating an Array from a CSV

      Operations an Array from a CSV

      Operations with NumPy Arrays

      Two-Dimensional Array

      Selecting Elements from 1-D Array

      Selecting Elements from 2-D Array

      Logical Operation with Arrays

      Indexing NumPy elements using conditionals

      NumPy’s Mean and Axis

      NumPy’s Mode, Median and Sum Function

      NumPy’s Sort Function and More

  • MatPlotLib
    • Bar Chart using Python MatPlotLib

      Column Chart using Python MatPlotLib

      Pie Chart using Python MatPlotLib

      Area Chart using Python MatPlotLib

      Scatter Plot Chart using Python MatPlotLib

      Play with Charts Properties Using MatPlotLib

      Export the Chart as Image

      Understanding plt. subplots () notation

      Legend Alignment of Chart using MatPlotLib

      Create Charts as Image

      Other Useful Properties of Charts.

      Complete Understanding of Histograms

      Plotting Different Charts, Labels, and Labels Alignment etc.

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  • Introduction to Seaborn
    • Introduction to Seaborn

      Making a scatter plot with lists

      Making a count plot with a list

      Using Pandas with seaborn

      Tidy vs Untidy data

      Making a count plot with a Dataframe

      Adding a third variable with hue

      Hue and scattera plots

      Hue and count plots

  • Visualizing Two Quantitative Variables
    • Introduction to relational plots and subplots

      Creating subplots with col and row

      Customizing scatters plots

      Changing the size of scatter plot points

      Changing the style of scatter plot points

      Introduction to line plots

      Interpreting line plots

      Visualizing standard deviation with line plots

      Plotting subgroups in line plots

  • Visualizing a Categorical and a Quantitative Variable
    • Current plots and bar plots

      Count plots

      Bar plot with percentages

      Customizing bar plots

      Box plots

      Create and interpret a box plot

      Omitting outliers

      Adjusting the whisk

      Point plots

      Customizing points plots

      Point plot with subgroups

  • Customizing Seaborn Plots
    • Changing plot style and colour

      Changing style and palette

      Changing the scale

      Using a custom palette

      Adding titles and labels: Part 1

      Face Grids vs. Axes Subplots

      Adding a title to a face Grid object

      Adding title and labels: Part 2

      Adding a title and axis labels

      Rotating x-tics labels

      Putting it all together

      Box plot with subgroups

      Bar plot with subgroups and subplots

      Well done! What’s next

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Validate your skills and knowledge by working on industry-based projects that includes significant real-time use cases.Gain hands-on expertize in Top IT skills and become industry-ready after completing our project works and assessments.Our projects are perfectly aligned with the modules given in the curriculum and they are picked up based on latest industry standards. Add some meaningful project works in your resume, get noticed by top industries and start earning huge salary lumps right away.
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FAQ's

Gain a competitive edge with industry-focused Python for Data Science courses at Croma Campus, ensuring practical skills and real-world applications.

Basic knowledge of programming and a strong desire to delve into the world of data science are recommended prerequisites for the Python for Data Science course.

Anyone with an interest in data science, including students, professionals, and enthusiasts, can register for the Python for Data Scientist course.

Experienced and industry-qualified instructors at Croma Campus will guide you through the Python for Data Scientist Course.

The course duration varies, but typically, it is designed to be completed within a reasonable timeframe, considering both learning depth and efficiency.

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