Get 100% refund (no questions asked ) if you don't like the course in first 7 days.

13 Weeks Programme.

Get Certificate and Projects Done.

100 % Placement/Job Support Till You Get A Job.

Get to know how real world project works.

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Course Details: Zero To Data Analyst

Learn with a Highly Structured, Personalized & Guided World-Class Program. To Become the Best Tech Professionals and get Placed at Top Product Based Companies.

Week 1 - Module 1: Introduction To Data Analysis & Visualization

As a Data Analyst, it is important we know how to break down business situations, design correct metrics & visualize the data.

Within this module, you will learn all of this.

Week 2 - Module 2: Tableau/ PowerBI

1 - Visual Analytics

2 - Charts, Graphs, Operations on Data & Calculations in Tableau/ PowerBl.

3 - Advanced Visual Analytics & Level of Detail (LOD) Expressions

4 - Geographic Advanced Charts, and Worksheet & Workbook Formatting

Week 3 - Module 3: Introduction To Python

1 - Flowcharts, Data Types, Operations

2 - Conditional Statements & Loops

3 - Strings

4 - In-build Data Structures - List, Tuples, Dictionary, Set, Matrix Algebra, Number Systems

Week 4/5 - Module 4: Python Libraries

1 - Numpy, Pandas

2 - Matplotlib

3 - Seaborn

4 - Data Acquisition

5 - Web API

6 - Web Scrapping

7 - Beautifulsoup

8 - Tweepy

Week 6 - Module 5: Introduction to Power BI

1 - Get Data From Different Data

2 - Profile The Data

3 - Clean Transform and Load the Data

4 - Design a Data Model

5 - Develop a Data Model

Week 7/8 - Module 5: Introduction to Power BI

1 - Optimize Model Performance

2 - Create Reports

3 - Create Dashboards

4 - Enhance Reports to Expose Insights

5 - Perform Advanced Analysis

6 - Manage Datasets

Week 9 - Project 1

Week 10- Project 1

Week 11 - Project 1

Week 12 - Module 6: Get Placed as Data Analyst at Top MNC/Companies

This process is usually in 3 phases:

1 - Build a strong profile

2 - Applying the right way

3 - Acing the interview

We focus on all the above 3 objects in this phase.

Building a strong profile

1 - Resume Creation

2 - LinkedIn profile optimization

3 - Profile creation on other platforms

Applying the right way

1 - Opportunities through Collaboration with 250+ tech companies

2 - Referral to almost all the top product companies

3 - Sharing hiring requirement of different companies

Acing the interview

1 - On Demand Mock interviews

2 - Online Interview Guidelines

3 - Salary Negotiation

Note: All topics taught in live classes with limited batch size helping in instant doubt support to accelerate learning. Assignment (post-lecture) & their evaluation.

Hyper-Personalised: Special focus on the individual with a constant touch from student success manager & mentor.

Course Details: Zero To Data Engineering

Module 1: AWS Cloud Computing

1 Introduction to Cloud Computing.

2 Cloud Deployment.

3 Cloud Providers and Case Studies

Module 2: SQL

1 Introduction to Databases & Snowflake Setup

2 Extracting data using SQL

3 Functions, Filtering & Subqueries

4 Joins

5 GROUP BY & Aggregation

6 Window Functions

7 Date and Time Functions & CTEs

8 Indexes & Partitioning

Module 3: Introduction To Python

1 Flowcharts, Data Types, Operations

2 Conditional Statements & Loops

3 Strings

4 In-build Data Structures - List, Tuples, Dictionary, Set, Matrix Algebra, Number Systems

Module 3: Python Libraries

1 Numpy, Pandas

2 Matplotlib

3 Seaborn

4 Data Acquisition

5 Web API

6 Web Scrapping

7 Beautifulsoup

8 Tweepy

Module 4: Snowflake Cloud Data Warehouse Setup and Introduction

1 - Introduction

2 - Getting started

Module 4.1 : Data Loading

4 - Loading data

5 - Copy options

6 - Loading unstructured data

7 - Performance optimization

Module 4.2 : Data Loading From Cloud Storage

8 - Loading from AWS

9 - Loading from Azure

10 - Loading from GCP

11 - Snowpipe

Module 4.3 : Snowflake Cloud Data Warehouse Features

12 - Time Travel

13 Fail Safe

14 - Types of tables

15 - Zero-Copy Cloning

16 - Data Sharing

17 - Data Sampling

18 - Scheduling Tasks

19 - Streams

20 - Materialized Views

21 - Dynamic Data Masking

22 - Access Management

Project 1

Project 2

Project 3

Note: All topics taught in live classes with limited batch size helping in instant doubt support to accelerate learning. Assignment (post-lecture) & their evaluation.

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