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Top-Rated Full-Stack Developer Course

Course Overview

Data Science is a multidisciplinary field that combines statistical analysis, machine learning, programming, and domain expertise to extract insights from structured and unstructured data. This course provides a comprehensive introduction to the fundamental concepts, tools, and techniques used in data science, equipping learners with the necessary skills to analyze data, build predictive models, and drive data-driven decision-making.

Frontend

Advanced Excel

Advanced Excel skills empower users to perform complex data analysis, create dynamic dashboards, and automate repetitive tasks using functions and macros. Mastery of pivot tables, VLOOKUP, and data visualization techniques in Excel enhances efficiency and decision-making capabilities.

Backend

SQL

SQL (Structured Query Language) is the backbone of database management, enabling users to query, manipulate, and manage large datasets. Proficiency in SQL allows for the extraction of meaningful insights from vast amounts of data, supporting data-driven decision-making in various industries.

Frontend

Power Bi

Power BI is a powerful business analytics tool that transforms raw data into interactive dashboards and reports. With its user-friendly interface and robust data visualization capabilities, Power BI helps organizations gain deeper insights, track key performance indicators, and make informed decisions.

Frontend

Tableau

Tableau is a leading data visualization software known for its ability to create compelling and interactive visual representations of data. Its drag-and-drop interface allows users to build insightful dashboards and share them seamlessly, making data analysis accessible to all skill levels.

Frontend

Pandas

Pandas is a versatile data manipulation library in Python, designed for data cleaning, transformation, and analysis. It provides data structures like DataFrames, which simplify handling and analyzing structured data, making it a staple for data scientists and analysts.

Backend

Numpy

Numpy is a fundamental library for numerical computing in Python, providing support for large, multi-dimensional arrays and matrices. It offers a wide array of mathematical functions to perform operations on these arrays, making it essential for scientific computing and data analysis.

Frontend

Power Query

Power Query is a data connection technology that enables users to discover, connect, combine, and refine data across a wide variety of sources. Integrated within Excel and Power BI, it streamlines the data preparation process, allowing for efficient data analysis and reporting.

Language

Python

Python is a versatile and widely-used programming language known for its readability and ease of use. Its extensive libraries and frameworks support a variety of applications, from web development to data science, making it an essential tool for modern developers and analysts.

COURSE OBJECTIVE

Understand the fundamentals of data science, its applications, and industry relevance.
Explore data preprocessing techniques, data visualization, and exploratory data analysis (EDA).
Apply machine learning algorithms for predictive modeling.
Work with Python and key data science libraries like Pandas, NumPy, Matplotlib, and Scikit-Learn.
Gain hands-on experience with data wrangling, feature engineering, and model evaluation.
Understand big data concepts and cloud-based data science workflows.
Develop proficiency in handling real-world datasets and creating actionable insights.

WHy Choose Us

Beginners and professionals looking to start a career in data science.
Software engineers and analysts who want to expand their knowledge of machine learning.
Business and marketing professionals interested in leveraging data for strategic decisions.
Students and researchers looking to enhance their analytical skills.

COURSE MODULES

➢ Introduction & Quantitative and aptitude prep

➢ Advanced Excel

➢ CV Session & Linkedin session

➢ SQL

➢ Power BI

➢ Python

➢ Introduction to Maths for Data

➢ ML Concepts & Recommendation

  • ➢ Capstone & End Projects

➢ Placement Preparation

FAQ

Who is this course suitable for?

This course is designed for beginners, professionals, and students who want to build a career in data science. Whether you have a background in IT, business, marketing, or finance, this course will help you develop essential data science skills. Basic knowledge of Python and mathematics is beneficial but not mandatory.

This course primarily focuses on Python as the programming language. You will also learn to work with data science libraries such as Pandas, NumPy, Scikit-Learn, Matplotlib, and Seaborn. Additionally, we will introduce big data and cloud technologies like Hadoop, Spark, and Google Cloud.

No, prior experience in data science is not required. However, familiarity with basic Python programming and statistics will be helpful. We cover essential coding concepts and provide hands-on exercises to help beginners learn quickly.

Yes! Upon successfully completing the course, including assignments and the final project, you will receive a Certificate of Completion, which you can showcase on LinkedIn, job applications, and resumes.

Yes! This course emphasizes practical learning, so you’ll get hands-on experience with Python, machine learning algorithms, and real-world datasets. You’ll work on coding assignments, mini-projects, and a final capstone project to solidify your knowledge.

Yes! You will have access to discussion forums, Q&A sessions, and community support to help you with doubts and coding challenges. Some premium courses also offer one-on-one mentorship or live sessions with industry experts.