Master the basics of Machine Learning in Python Course. Join now to learn under a Python and ML expert.
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Corporate Served- 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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Plenary for Machine Learning with Python 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 |
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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
- Introduction To Python
Installation and Working with Python
Understanding Python variables
Python basic Operators
Understanding the Python blocks.
- Python Keyword and Identiers
- Arithmetic
- Relational
- Logical
- Assignment
- Membership
- Identity
Python Keyword and Identiers
Python Comments, Multiline Comments.
Python Indentation
Understating the concepts of Operators
- 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
- Strings
- List
- Tuples
- Dictionary
- Sets
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
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
- 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)
- 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.
- 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
- 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
+ More Lessons
Mock Interviews
Projects
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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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Testimonials & Reviews
1. In recent times Python learning is hugely in demand. And I was looking for an institution to get myself enrolled in this course to become a Data Scientist. They have the best trainers and an affordable fee structure. It's been month
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Enrolling yourself in the Deep learning certification program of Croma Campus is the best way to master all the concepts of data science and deep learning. My experience with these people has been very amazing and positive. The support
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Data Science
Hello, I have joined Croma Campus for a few months in the course helped in acquiring good knowledge. Also, there are many extra classes held by the trainer. There are many mock sessions given after the post completing the course. The s
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Data Science
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Data Science
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I have joined Croma Campus for taking the Masters in Data Science. It is a good place to learn. Helps in gaining the skills & knowledge.
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