Learn how to use Python for data analysis. Join today to learn under the mentorship of an expert data scientist.
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Corporate Served- 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.
- 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.
Comprehensive Python and mathematics training
Industry-experienced trainers
Interactive group discussions and debates
100% placement guarantee
Python for Data Science Training in Chennai
- 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.
- 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.
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.
- 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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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 |
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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
- 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
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
- 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
Mock Interviews
Projects
Phone (For Voice Call):
+91-971 152 6942WhatsApp (For Call & Chat):
+918287060032self assessment
Learn, Grow & Test your skill with Online Assessment Exam to achieve your Certification Goals
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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Assignment
Adding the scope of improvement and fostering the analytical abilities and skills through the perfect piece of academic work.
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