Data Analytics Online Course

Decision Making with Data Analytics

Turn Data into Insights: Master Data Analytics for Informed Decision-Making

Become an Expert in

Data Analytics

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The Data Analytics course at BharatSkillz is designed to provide a comprehensive understanding of data analysis techniques and tools. You’ll learn to collect, clean, and analyze data to uncover valuable insights that drive business success. With a focus on both descriptive and predictive analytics, this course equips you with the skills needed to make data-driven decisions. Through hands-on projects and real-world case studies, you’ll develop expertise in data visualization and big data tools, preparing you for a successful career in data analytics.

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Data Analytics Course Syllabus

To begin with, excel is a fundamental tool for data analysis, and mastering its functionalities is essential for any data analyst. Such a course should cover the following key areas:

  • Understanding the role of business analytics in decision-making
  • Mastering Excel functions for data analysis, including conditional formatting and pivot tables
  • Applying statistical methods such as hypothesis testing and regression analysis
  • Visualizing data using charts and dashboards
  • Introduction to advanced analytical tools like Power BI

Structured Query Language (SQL) is a standard language for managing relational databases. A course in SQL fundamentals covers the following topics:

  • Basics of databases and their interrelationships
  • Proficiency in SQL commands for data manipulation and retrieval
  • Creation of tables, views, and stored procedures
  • Advanced SQL topics like joins, subqueries, and user access controls

Python is one of the most versatile programming languages widely used for data analysis and machine learning. A course in Python programming covers the following:

  • Importing, cleaning, and preprocessing data
  • Manipulating data using libraries like NumPy and Pandas
  • Performing statistical analysis and building machine learning models
  • Developing data pipelines for analysis and visualization

R is a powerful programming language and environment for statistical computing and graphics. A course in R programming must cover the following areas:

  • Fundamentals of R programming and data structures
  • Handling data frames, lists, and arrays
  • Implementation of statistical methods and data visualization techniques

Tableau is a leading data visualization tool for creating interactive dashboards and reports. A course in Tableau covers the following:

  • Introduction to tableau and its core concepts
  • Creating various types of visualizations, including charts and graphs
  • Building interactive tableau dashboards and visual stories
  • Data blending and formatting techniques for effective visualization

Power BI is a business analytics tool by Microsoft that provides interactive visualizations and business intelligence capabilities. A course in Power BI covers the following:

  • Creating and managing interactive reports and dashboards
  • Utilizing advanced features like Quick Insights and natural language queries
  • Best practices for data layout, visualization, and collaboration using Microsoft Teams

An ideal data analyst full syllabus must also include a capstone project. A capstone project allows students to apply their skills to solve a real-world problem, showcasing their expertise to potential employers. The project should demonstrate proficiency in data analysis, visualization, and problem-solving.

Starting a career as a data analyst requires dedication, continuous learning, and hands-on experience. Here are some steps to get started:

1. Upskilling

Enroll in online courses and certifications covering the essential components of a data analyst syllabus. Choose reputable institutions or online platforms offering comprehensive training programs.

2. Gaining Practical Experience

Gain practical experience by working on real-world projects, participating in internships, or contributing to open-source projects. The right data analyst syllabus will offer you industry projects to help you gain hands-on experience.

3. Networking

Build a professional network within the data analytics community by attending industry events, joining online forums, and connecting with professionals on professional networking platforms like LinkedIn.

A career in data analytics can be incredibly rewarding for those who enjoy using data to make decisions and solve problems. If you wish to master data analytics, pursuing a Post Graduate Program in Data Analytics can provide you with advanced knowledge and comprehensive learning, practical projects, and mentorship from industry experts, which are invaluable for deepening your understanding and enhancing your employability. You can also choose from a wide range of data analyst courses to find the one that best suits your needs.

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Data Analytics Course Fee

Top-quality learning that’s easy on your pocket.
Aayushi Sharma
Aayushi Sharma
AI Developer
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Bharat Skillz offers clear, practical courses with real-life applications. The projects really helped me understand the concepts better. Highly recommended!

Self Paced

You’ll Get Access to:
4999
  • Internship Certificate by Co-Branded Company
  • 1 Minor + 1 Major project
  • LIVE INTERACTIVE SESSIONS
  • Recorded Modules
  • 25+ hours of video content access
  • Certificate on successful completion
  • Training Certificate from Bharat Skillz

Mentor Led

Everything in Self Paced, Plus:
9999
  • Internship Certificate by Co-Branded Company
  • 1 Minor + 1 Major project
  • LIVE INTERACTIVE SESSIONS
  • Recorded Modules
  • 25+ hours of video content access
  • Certificate on successful completion
  • Training Certificate from Bharat Skillz
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FAQ's

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Python basic Python concepts & terms Python fundamentals Python data structure & modules

Pandas & visualization

Introduction to probability theory Distribution central limits theorem & hypothesis testing

Introduction to Artificial intelligence Applications of Artifiticial intelligence Hands on work with Python

Introduction to Neuron deep learning (basics & scope) Evolution of deep learning Applications of Deep learning Machine learning Vs. Deep learning Techniques & types of deep learning Introduction to ANN

Neuron Diagram Neuron Models & NETWORK FUNCTIONS of Neurons activation Functions of Gradient descent & Stochastic Ramp function & sigmoid function & Gaussian function

Perceptron & multilayer network Backpropagation Deep neural network installing libraries Creating ANN python Training the model

Introduction to open Cv (Image processing) Learning basic image manipulations Introduction to CNN CNN Institution Convolution Operation pooling Flattering building a CNN using python Training the model

Introduction to open Cv (Image processing) Learning basic image manipulations Introduction to CNN CNN Institution Convolution Operation pooling Flattering building a CNN using python Training the model

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