Learn how to use Python with Data Science Course. Join today to learn under the mentorship of an expert data scientist.

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  • Python is basically an open-sourced, interpreted, high-level language that is extensively used for object-oriented programming. In fact, it is one of the most-widely languages utilized by data scientists hugely for numerous Data Scientists and their applications respectively. Moreover, Python presents extraordinary performance to deal with mathematics, statistics, and scientific characteristic. If you also dream to turn into a Data Scientist, then you must have detailed information concerning Mathematics, Python, and its implementation precisely.
    • Here, you will get a probability to gather training from industry-experienced experts conserving numerous years of experience in the applicable fields.

      Furthermore, here, our trainers will information you related to its stipulations as well.

      Along with training, we will additionally guarantee you 100% placement.

      You will get hold of in-depth training as well.

  • Along with training, you will experience a whole new learning experience. In fact, our trainers will indulge you in various kinds of group discussions, and debates to know your understandability of yours concerning this subject.

Python for Data Scientist Training


  • After enrolling in our courses, you will discover our course content being constructed as per the latest features, specifications, and trends. In a way, you will get ample opportunities to learn new things.
    • Our trainers will teach you this subject right from the scratch.

      They will inform you of the use of "Expressions, and Variables. Describe Data Structures in Python including Lists, Tuples, Dictionaries, Sets, etc.

      Further, they will also explain to you the utilization and implementation of Loops, Functions, Objects & Classes. Work with data in Python using Pandas and NumPy libraries respectively.

      You will not only receive theoretical information but also get the chance to receive its practical information as well.

      You will be provided with study material also.

  • Moreover, getting started with our online certification will resource you to accumulate some hidden data involving this Data Science Course
    • In a way, you will in addition reap its stipulations appropriate from the scratch.

      With having this legit accreditation in hand, it will be worthwhile to proceed to be regular in this course for a longer time.

      Our trainers will in addition aid you to get positioned in a specific company.

      To be accurate, by acquiring its in-depth information, you will get a chance to earn around 10.2 lakhs INR per annum respectively.

  • Data Scientists are hugely in demand in the market, and by choosing this direction, you will get a fair opportunity to acquire its exposure. This direction will also give you chance to shine and be at the top of your career.
    • By obtaining this legit certification in hand, your probability of getting settled into an organization will increase.

      Furthermore, by way of the potential of imbibing its particular information, you will shortly turn into a professional in this field.

      Moreover, as a freelancer also, you will be successful to make an acceptable respectable extent of money.

      In fact, your chances of getting settled into a multi-national company will increase.

      By obtaining this accreditation, your skills will get validated and you will be able to work professionally as a Data Scientist.

  • There are various reasons to choose this certification. One of the significant reasons is its high demand, bright scope, and increased utilization in numerous sectors. If you want to turn into a successful Data Scientist, then you should surely obtain this accreditation.
    • Your mathematical, and statistical skills will get polished.

      Moreover, your programming skills will also get enhanced.

      You will turn into a skilled Data Scientist.

      You will acquire its minute details.

      Moreover, this accreditation will also help you in getting settled with huge establishments like TCS, IBM, etc.

  • Well, a Data Scientist is entitled to perform a lot of tasks, one of their main tasks includes handling huge volumes of data. You must know what you might get indulged in after turning into a Data Scientist.
    • Your foremost duty will be to make use of raw data and extract valuable information from it.

      You will also have to interpret large data sets.

      Furthermore, your job role will also include giving some business-driven decisions by analysing the data.

      In fact, your job role will also be to execute automated data collection and management process.

      In a way, you will also have to indulge in processing, and cleansing of data.

  • Here are some of the top organizations hiring for Data Scientist:
    • IBM, TCS, Accenture, Wipro, Amazon, Cognizant, etc, are the top companies hiring skilled Data Scientists.

      Opting for this specific field will be beneficial for you in numerous ways.

      In fact, by obtaining this accreditation, your career graph will get uplifted.

      You will acquire a highly-secure position for yourself.

      You will also receive a higher salary package.

  • Advantages of Completing the Data Science Certification Course at Croma Campus:
    • By entering Croma Campus, you will get a wide range of certifications belonging to different industries.

      You will find our accreditations being extensively accepted by the IT territory.

      Obtaining accreditation from Croma Campus will assist you to get settled into a good workspace.

      Moreover, here, you will receive an interactive sort of training, that will also improve your communication skills.

      We will give you access to the Learning Management System, where you will be able to see your performance, go through your class videos, assignments, etc.

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Plenary for Python for Data Scientist Training

Track Week Days Weekends Fast Track
Course Duration 40-45 Days 7 Weekends 8 Days
Hours 1 Hrs. Per Day 2 Hrs. Per Day 6+ Hrs. Per Day
Training Mode Classroom/Online Classroom/Online Classroom/Online
Course Price at :
10% OFF Expires in01D 08H 53M 23S

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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.






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

                  How to use nested IF and Else in Python


                  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


                  Lots of Example on Python Calendar

                  Create 12-month Calendar



                  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






                  Interquartile range


                  Standard Deviation


                  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


                  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


                  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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              Prepare & Practice for real-life job interviews by joining the Mock Interviews drive at Croma Campus and learn to perform with confidence with our expert team.Not sure of Interview environments? Don’t worry, our team will familiarize you and help you in giving your best shot even under heavy pressures.Our Mock Interviews are conducted by trailblazing industry-experts having years of experience and they will surely help you to improve your chances of getting hired in real.
              How Croma Campus Mock Interview Works?


              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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              This course will hardly take your 3 months to fully get into its detailing.

              It's not mandatory though, but it will be appreciable if you will belong from the computer-science background.

              The training will be imparted by industry experts holding numerous years of experience in this field.

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