Follow Us On:

Python

Python Programming

Key Focus Areas:

  • Install python (Anaconda)
  • Jupyter Notebook
  • Install Numpy, Pandas, MatplotLib, Seaborn and SciKit Learn
  • Spyder IDE
  • Basics of Data Processing
    • Strings
    • Lists
    • 5Tuples
    • Sets
    • Dictionaries
    • Control Flows
    • Functions
    • Formal, Positional, Keyword arguments
    • Predefined functions (range, len, enumerates etc…)
  • Data Frames
  • Packages required for data Science in R and Python.

NumPy package

  • One-dimensional Array
  • Two-dimensional Array
  • Pre-defined functions (arrange, reshape, zeros, ones, empty)
  • Basic Matrix operations
  • Scalar addition, subtraction, multiplication, division
  • Matrix addition, subtraction, multiplication, division and transpose
  • Slicing
  • Indexing
  • Looping,/li>
  • Shape Manipulation

Pandas package

  • Series,/li>
  • Data Frame
  • Group By
  • crosstab
  • apply

Data Preparation Techniques

  • Structured Data Preparation
  • Data Type Conversion
    • Category to Numeric
    • Numeric to Category
  • Data Normalization: 0-1, Z-Score
  • Skew Data handling: Box-Cox Transformation
  • Missing Data treatment.

Exploratory Data Analysis (EDA)

  • Statistical Data Analysis
  • Exploring Individual Features
  • Exploring Bi-Feature Relationships
  • Exploring Multi-feature Relationships
  • Feature/Dimension Reduction: Principal Component Analysis
    • PCA advantages
    • Interpretation of PCA output
  • Covariance & Correlation
  • Relating PCA to Covariance/Correlation.

Feature Engineering (FE)

  • Combine Features
  • Split Features.
Embark on a transformative journey into the world of data science with our comprehensive course focused on Python programming. Dive into Python’s versatility and power, mastering essential libraries like NumPy, Pandas, and Matplotlib. Explore data analysis, machine learning, and statistical modeling , gaining hands-on experience through practical projects. Our curriculum is crafted by industry experts, ensuring relevance to current trends and demands. Whether you’re a beginner or seeking to enhance your skills, our course provides a structured learning path. Immerse yourself in the intricacies of data manipulation, visualization, and predictive modeling . By the course’s end, you’ll possess the proficiency to tackle real-world data challenges and leverage Python’s capabilities in diverse industries. Join us in unlocking the potential of data science with Python, and empower yourself to thrive in the dynamic landscape of data-driven decision-making. Elevate your career and make impactful contributions with our Data Science with Python course.

What is python ?

Python is a general-purpose programming language, which means that, unlike JavaScript, HTML, and CSS, it can be used in applications beyond web development. Though it’s been around for 30 years, it has recently become one of the most popular programming languages, and its popularity continues to grow.

What You Can Do With Python ?

Python is an excellent choice for anyone looking to get into app development. It’s an ideal language for prototyping because of its lower development time and effort. As with web development, app development is made easy by Python’s cross-platform abilities. Specifically, Python has recently become popular in the fast-growing sectors of blockchain app development and gaming app development thanks to its robust frameworks and real-time testing.

Since Python is such a flexible programming language, it can make it easier to build complex web utilities. Python’s various web frameworks are especially useful — like the popular Django, which can make building both back end and client-side functionality easier and faster. Even large companies use Python for web development; both Google and YouTube have used it extensively for many of their digital infrastructures.

Python's readability and ease of use make it an ideal language for beginners, while its scalability and performance make it suitable for complex projects. The Python language career offers great scope. The demand for Python developers continues to grow, offering a promising job market and competitive salaries. Developers use it for web and software development. Data scientists leverage it for data analysis, machine learning, and AI. Network engineers employ it for network automation. In finance, Python aids quantitative analysis. It's versatile, powering diverse applications, making it integral in technology, finance, healthcare, and more.

In AI and ML, Python is a dominant language. Its simplicity and extensive libraries, including TensorFlow and PyTorch, facilitate the development, training, and deployment of machine learning models. Python's versatility supports tasks like natural language processing, computer vision, and reinforcement learning, making it the preferred choice for AI and ML practitioners. Popular frameworks, community support, and a rich ecosystem contribute to Python's prominence in creating sophisticated and scalable artificial intelligence solutions.

Have Any Query?

Get A Quote

    Experience our courses and enhance your skills

    User can click on get started by entering there user details like currently we have

    Frequently Asked Question

    AI in data science automates complex tasks like pattern recognition and predictive modeling. Machine learning algorithms analyze vast datasets to uncover insights, make predictions, and optimize decision-making. AI enhances data processing efficiency, enables advanced analytics, and supports data-driven decision-making, revolutionizing the field of data science.

    In general programming, we have the data and the logic by using these two we create the answers. But in machine learning, we have the data and the answers and we let the machine learn the logic from them so, that the same logic can be used to answer the questions which will be faced in the future. Also, there are times when writing logic in codes is not possible so, at those times machine learning becomes a saviour and learns the logic itself

    "With our data science course, you'll master essential skills in Python, power BI and machine learning. Analyse data, create insightful visualizations, and apply statistical techniques. Gain hands-on experience with real-world projects, fostering critical problem-solving skills. Acquire the knowledge to excel in diverse data-driven roles and drive innovation in any industry.

    Python is known for its simplicity, readability, and versatility. It supports object-oriented, imperative, and functional programming styles. Its extensive standard library facilitates diverse tasks. Dynamic typing and automatic memory management enhance development speed. Python is widely used for web development, data science, machine learning, and automation.

    content 11