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Master the Fundamental Concepts of Python Course. Enroll today and become a skilled Python Course expert.

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Course Duration

32 Hrs.

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2 Project

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  • The Python Course in Canada is designed to teach you Python, one of the most versatile and popular programming languages in the world today. Python is used in a variety of fields such as Data Science, Web Development, Machine Learning (AI), and Automation. Whether you're just starting or have some experience in programming, this course will teach you everything from Python basics to advanced concepts. You'll be able to write Python code, develop software, analyze data, and build real-world projects. Its an ideal choice for anyone looking to enter the technology field or upgrade their skills.

Python Course in Canada

About-Us-Course

  • By the time you complete the Python Training in Canada, you will achieve the following objectives:
    • Understand Python Syntax: Learn how Python works, including how to write simple code, use loops, and create functions.

      Master Python Data Structures: Youll understand how to use lists, dictionaries, tuples, and sets to store and manage data efficiently.

      Work with Object-Oriented Programming (OOP): Learn to design and organize your code into reusable objects and classes.

      Build Real-World Projects: From building a web scraper that collects information from websites to creating interactive web applications, you will work on projects that solve real-world problems.

      Explore Popular Libraries and Frameworks: You will work with libraries like NumPy, Pandas, Matplotlib, and frameworks like Flask and Django to make development easier and faster.

      Understand Code Efficiency: Focus on writing code that is optimized, clean, and easy to understand while solving real-world problems.

  • Freshers with a Python Training in Canada can expect the following salary range in Canada:
    • Starting Salary: New graduates or beginners can earn CAD 50,000 - CAD 65,000 per year (roughly 30,00,000 - 39,00,000 in Indian Rupees).

      With Experience: After gaining a few years of experience, your salary can go up to CAD 70,000 - CAD 90,000per year (approximately 42,00,000 - 54,00,000).

  • Once you have completed the Python Training in Canada, heres what you can expect for your career growth:
    • Entry-Level Roles: You will be qualified to start as a Junior Python Developer, Software Developer, or Web Developer.

      Mid-Level Roles: With some work experience, you can move to higher roles like Senior Python Developer, Data Scientist, or Automation Engineer.

      Advanced Specializations: You can further specialize in areas like Machine Learning, Artificial Intelligence, or Data Engineering.

      Leadership Roles: With several years of experience, you can move into roles like Tech Lead, Engineering Manager, or Solutions Architect.

  • The Python Training in Canada is widely popular for a few key reasons:
    • High Demand for Python Developers: Python is used across many sectors like Data Science, Web Development, and Machine Learning, making developers highly sought after.

      Ease of Learning: Python is known for its simple and clean syntax, which makes it easier to learn for beginners and experienced developers alike.

      Versatility: Python can be used for a wide range of projects, from building websites to working with big data, making it an all-purpose programming language.

      High Salaries: Python developers are paid well in Canada, and as the demand for Python grows, so do the salary opportunities.

  • Once you complete the Python Training in Canada, you will be qualified for several exciting job roles, such as:
    • Python Developer: Writing Python code to build applications, websites, or backend systems.

      Data Scientist: Using Python to collect, clean, and analyze data to uncover trends and help businesses make decisions.

      Machine Learning Engineer: Developing algorithms and machine learning models using Python libraries like TensorFlow and Scikit-learn.

      Web Developer: Building websites and web apps using frameworks like Flask or Django.

      Automation Engineer: Writing Python scripts to automate repetitive tasks and processes in industries like software development, finance, and more.

  • Python developers are in demand across multiple industries, including:
    • Technology & Software Development: Python is the main language used to create software applications, websites, and tools.

      Data Science and AI: Data scientists and AI engineers use Python to build algorithms and machine learning models.

      Finance: Python is used for building trading algorithms, financial data analysis, and risk management models.

      Healthcare: Python is used for analyzing medical data and building healthcare applications.

      E-Commerce: Many online businesses use Python to build websites and manage user data.

  • Upon completing the Python course, you will earn certifications that help prove your skills to employers.
  • The Python course fee in Canada varies based on the institution and course duration:
    • Average Course Fee: CAD 500 - CAD 1,500 (approximately 30,000 - 90,000).

  • Upon completing the course, you can opt for an official certification, which adds value to your resume. The cost of official certifications generally ranges between:
    • Official Certification Fee: CAD 100 - CAD 250 (approximately 6,000 - 15,000).

  • During this course, you will work on hands-on projects that help solidify your skills:
    • Web Scraper: A tool built with Python to collect data from websites.

      Data Analysis: Use libraries like Pandas and Matplotlib to analyze large datasets and create visualizations.

      Web Development: Build a website using the Flask or Django framework.

      Machine Learning: Learn to develop a simple machine learning model using Scikit-learn to make predictions.

  • After completing the Python Training in Canada, we offer full support in helping you get a job:
    • Career Counseling: Receive guidance on how to create an effective resume and cover letter to showcase your Python skills.

      Interview Preparation: We offer mock interviews where you can practice and get feedback, so you feel more confident during real interviews.

      Job Referrals: We connect you with companies actively looking for Python developers and refer you for available positions.

      Job Search Assistance: We help you understand how to find job openings, apply effectively, and communicate with employers.

      Placement Assistance: With our guidance and your skills, youll have a better chance of securing a great job in Python development.

Why Should You Learn Python?

Not just learning –

we train you to get hired.

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CURRICULUM & PROJECTS

Python Training Program

    What is Data Analytic

    Common Terms in Data Analytics

    What is data

    Classication of data

    Relevance in industry and need of the hour

    Types of problems and business objectives in various industries

    How leading companies are harnessing the power of analytics

    Critical success drivers.

    Overview of Data Analytics tools & their popularity.

    Data Analytics Methodology & problem-solving framework.

    List of steps in Data Analytics projects

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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 Comments, Multiline Comments.
    • Python Indentation
    • Understating the concepts of Operators
      • Arithmetic
      • Relational
      • Logical
      • Assignment
      • Membership
      • Identity
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    Introduction to Statistics

    • Categorical Data
    • Numerical Data
    • Mean
    • Median
    • Mode
    • Outliers
    • Range
    • Interquartile range
    • Correlation
    • Standard Deviation
    • Variance
    • Box plot

    Understanding Statistics

    • Descriptive Statistics
    • Sample vs Population Statistics
    • Random variables
    • Probability distribution functions
    • Expected value
    • Normal distribution
    • Gaussian distribution
    • Z-score
    • Spread and Dispersion
    • Correlation and Co-variance

    Data Pre-Processing & Data Mining

    • Data Preparation
    • Feature Engineering
    • Feature Scaling
    • Datasets
    • Dimensionality Reduction
    • Anomaly Detection
    • Parameter Estimation
    • Data and Knowledge
    • Selected Applications in Data Mining

    EDA (Exploratory Data Analysis)

    • Need for structured exploratory data
    • EDA framework for exploring the data and identifying any problems with the data (Data Audit Report)
    • Identify missing data
    • Identify outliers’ data
    • Imbalanced Data Techniques
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    Data Analysis and Visualization using 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 Data Frame 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)

    Data Analysis and Visualization using 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

    Data Analysis and Visualization using 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 Data Visualization with 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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32 Hrs.
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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?

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FAQ's

No, this course is beginner-friendly and starts from the basics. It’s suitable for people with no prior programming experience.

The course typically lasts for 6-8 weeks, depending on your pace.

You can work as a Python Developer, Data Scientist, Machine Learning Engineer, Web Developer, or Automation Engineer.

Yes, you will receive a Certified Python Developer certification after completing the course.

Yes, there are free resources available, but a structured course with practical projects and certifications offers much more value and better career opportunities.

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  • - Get Tips from Trainer to Clear Interviews
  • - Attend Mock-Up Interviews with Experts
  • - Get Interviews & Get Hired

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