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


  • 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.

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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
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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 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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                        • 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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                        + More Lessons

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                        Mock Interviews

                        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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                        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.

                        Career Assistancecareer assistance
                        • - Build an Impressive Resume
                        • - Get Tips from Trainer to Clear Interviews
                        • - Attend Mock-Up Interviews with Experts
                        • - Get Interviews & Get Hired
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