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Master the basics of Machine Learning in Python Course. Join now to learn under a Python and ML expert.

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  • Machine Learning Using Python is hugely in demand nowadays. It is basically a legit procedure of making the computer analyse from studying data and statistics. Machine Learning is a step into the route of artificial intelligence (AI). Machine Learning is an application that analyses information and learns to predict the outcome. In the IT territory, it has been doing exceedingly well, because of its exceptional offerings, and implementations. In fact, it's genuinely in demand in various sectors as well.
  • In recent times, it has made a remarkable place for itself. If you also want to analyse this subject intently, then you should surely get in touch with Croma Campus. Yes, here, you will receive a detailed sort of training.
    • Here, at Croma Campus, you will receive whole new learning, and accepting environment.

      Along with training, you will be assured 100% placement as well.

      Moreover, here, you will find more than 140+ courses.

      Our trainers will also help you to imbibe its prerequisites as well.

Machine Learning Using Python

About-Us-Course

  • After enrolling in Python Machine Learning courses, you will find out our course content material being developed as per the trendy skills.
    • By enrolling in our course, you will get the opportunity to imbibe some latest market trends and features.

      Our trainers will impart training concerning its basics right at the beginning of the course.

      Furthermore, you will be explained about its various types of machine learning.

      Our experts will also give you a session of its different algorithms, and implementations.

      You will also receive information concerning How statistical modelling relates to machine learning and how to compare them.

      They will explain the whole subject with various instances as well.

  • To be honest, there is a big demand for Machine Learning in the market, and holding its accreditation will give you opportunities to make good money out of it.
    • By graduating from our institution, you will end up getting into a good organization.

      With having a legitimate certification in hand, you will eventually grab a decent salary package.

      Our trainers will also thoroughly train you to crack the interview.

      In fact, you will get loads of opportunities to learn new things.

      To be exact, you will earn around approximately 8,42,482 and can work as a Machine Learning Engineer professionally.

  • By attentively imbibing its details, you will get the opportunity to make positive growth in your career. You might even end up reaching the peak of your career.
    • By obtaining this accreditation in hand, your chances of getting into a multinational company will increase.

      Even working as a freelancer also, you will make a good living out of it.

      Moreover, by acquiring experience working in a company, you can end up opening your own start-up.

      With imbibing the latest skills, your salary bracket will also increase.

      Your market value will eventually increase.

  • There are numerous reasons to opt for Machine Learning Using Python course. Moreover, it will give you various chances to learn new things fields as well.
    • Python Machine learning both are in demand, and imbibing its details, and in-depth information will only boost your career graph. Choosing this direction will be fruitful for your career in numerous ways.

      Enrolling in this course will give you a lot of opportunities to imbibe your skills right from the scratch.

      Our trainers will help you to imbibe information concerning its basics, Python Ecosystems, and Methods for Machine Learning.

      In fact, they will also impart training regarding Data Loading for ML Projects, understanding Data with Statistics, procedure of Data with Visualization.

      You will also acquire knowledge of different methods of Machine Learning respectively.

      Apart from this, you will always be under the guidance of industry-experts, and they will be there to solve your query.

  • Well, a Machine Learning Engineer is entitled to perform a number of tasks. Your duties will also depend upon the kind of project you are indulging in. Some of the main job roles are listed below.
    • Working as a Machine Learning Engineer will indulge you into constructing ML machines.

      In fact, your job role will also include researching and implementing ML algorithms and tools respectively.

      Choosing appropriate data sets will also be your foremost job role.

      You will be responsible for transforming data science prototypes.

      Working with ML libraries will also be your important job role.

      You will have to develop Machine Learning based applications as per your clients' needs and requirements.

      You will have to take in your team mates suggestions as well.

  • Here are some of the top organizations hiring for Machine Learning Engineer:
    • Amazon, Databricks, TCS, Accenture, IBM, Prolific are the top companies hiring skilled Machine Learning Engineers.

      Opting for this specific subject will be really useful for you in numerous ways.

      In fact, by means of acquiring this accreditation, your profession graph will get uplifted.

      You will collect a highly-secure role for yourself.

      You will additionally grab an increase salary package.

  • Advantages of getting Certification after complete the Machine Learning Course in Delhi.
    • You will find our all courses being extensively accepted by the industries.

      In fact, here, you will find numerous sorts of courses belonging to different sections.

      Along with acquiring this accreditation, you can obtain another accreditation as well.

      Graduating from Croma Campus will hugely help you in getting settled in a well-established company.

      Your career graph will also get uplifted.

Why you should choose Machine Learning in Python Course?

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CURRICULUM & PROJECTS

Machine Learning with Python Training

  • Machine learning is important because it gives enterprises a view of trends in ustomer behavior and business operational patterns, as well as supports the development of new products. Many of today's leading companies, such as Facebook, Google and Uber, make machine learning a central part of their operations
  • In this program you will learn:
    • Python Training Curriculum

      Data Analysis and Visualization using Pandas.

      Data Analysis and Visualization using NumPy and MatPlotLib

      Introduction to Data Visualization with Seaborn

      Machine Learning

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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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  • Introduction to Machine Learning
    • Articial Intelligence

      Machine Learning

      Machine Learning Algorithms

      Algorithmic models of Learning

      Applications of Machine Learning

      Large Scale Machine Learning

      Computational Learning theory

      Reinforcement Learning

  • Techniques of Machine Learning
    • Supervised Learning

      Unsupervised Learning

      Semi-supervised and Reinforcement Learning

      Bias and variance Trade-off

      Representation Learning

  • Regression
    • Regression and its Types

      Logistic Regression

      Linear Regression

      Polynomial Regression

  • Classication
    • Meaning and Types of Classication

      Nearest Neighbor Classiers

      K-nearest Neighbors

      Probability and Bayes Theorem

      Support Vector Machines

      Naive Bayes

      Decision Tree Classier

      Random Forest Classier

  • Unsupervised Learning: Clustering
    • About Clustering

      Clustering Algorithms

      K-means Clustering

      Hierarchical Clustering

      Distribution Clustering

  • Model optimization and Boosting
    • Ensemble approach

      K-fold cross validation

      Grid search cross validation

      Ada boost and XG Boost

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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.
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Projects

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

Yes, you will be given a free demo live session by our trainer, and after feeling satisfied with the training only, you will get enrolled in the course.

Well, the cost is pretty much affordable. Somewhere it comes around 537.82 USD, but to know the exact price, you will have to reach our counselling team.

Yes, we will provide all the important study material on our LMS portal.

It's not mandatory though, but it will be preferably okay if you will come from a computer-science background.

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