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Data Science Certification Program

Data Science Certification Program

Data Science Certification programs and Machine Learning are the hottest skills in demand” but wait it’s challenging too to learn. 

Today Data Science and Machine Learning are used in almost all industries, including automobile, banking, healthcare, media, telecom, and others.

As Data Science and Machine Learning practitioners, you will have to research and look beyond normal problems, you may need to do extensive data processing. experiment with the data using advanced tools and build amazing solutions for business. However, where and how are you going to learn these skills required for Data Science and Machine Learning?

Data Science and Machine Learning require in-depth knowledge of various topics. Data Science is not just about knowing certain packages/libraries and learning how to apply them. Data Science and Machine Learning require an in-depth understanding of the skills:- Basic to Advanced Excel, My SQL / SQL Server, Tableau, Python, and R Language. 

(8K+ Satisfied Learners)
To become a data scientist, or to get any job in data science, it is a good idea to get a data science certification. A certification (or certificate) will provide you with the necessary knowledge and skills to succeed as a data scientist
What are the Benefits of being a Data Scientist?
  • Machine learning, deep learning, and artificial intelligence application and implementation.
  • Mathematical and statistical knowledge.
  • Well-versed in data visualization, data analytics, data cleaning, and big data.
  • Good communication skill.
  • Excellent organizational skills.
The interviewer will test everything that you have mentioned in your skillset. Therefore, if you choose to go ahead with a data science certification, make sure that you keep up with your classes and gain the right skills.Your certificate won’t get you the job, skills will

Instructor -Led Online & Physical Classes

Batch Start DateLocationUpcoming SlotsTimings
10th Sep 2023Online & OfflineSold Out
10:30 AM to 12:30 PM
24th Sep 2023Online & OfflineFilling Fast
Weekend batch
14th Oct 2023Online & OfflineSAT & SUN
Weekend Batch

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INR 1,02,430/-
INR 42,000/- + 18% GST

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Course Content

For the curriculum, you will cover  in this course, click on the tab to check the detailed content

Module 1:- Getting Started with Excel

  • Introduction to Excel 2013/2016/2019/Office 365
  • Application Interface and Key Components of Excel
  • Navigating Through Excel Ribbon Tabs
  • Exploring Important Excel Options*
  • Live Session Exercise
  • Splitting data of Single Column into multiple
  • 10 Examples to use Auto-fill and Flash Fill
  • Magic of Go-To Special
  • Merge/Unmerge Cells & Wrap Text
  • Extracting Unique Values & Important Ribbon, General and Data Entry Keyboard Shortcuts

Module 2:- Formatting Essentials

  • Formatting Essentials Introduction
  • Custom Cell Number Formats
  • Custom Date/Time Formats
  • Working with Comments / Notes
  • Format Painter – A Quick way to copy ‘Formatting Attribute’
  • Paste Special
  • Table, Table Styles & Formatting
  • Freeze Panes

Module 3:- Functions & Formulas

  • Introduction to Excel Functions and Formulas
  • Basics of Functions & Formulas
  • Working with Cell References Types
  • Most Used Basics & Advanced Functions & Formulas
  • Working with Array Formulas
  • Creating Customized Formulas Step-by-Step with Live examples
  • Creating and Working with Dynamic Ranges using Function and Excel Table features
  • Formulas Debugging / Formulas Auditing
  • Types of Formula Errors / Error Handling Tricks
  • Date & Time Functions: – DATE, DAYS, TIME, NOW, WEEKNUM, WORKDAY, and WORKDAY.INTL etc.
  • Statistical Functions: – AVERAGE, COUNT, COUNTA, COUNTBLANK, MAX, MIN, LARGE etc.
  • Logical Functions: – IF, IFS, AND, OR, and IFERROR.
  • Newly Introduced Functions in Recent Version of Excel*: – CONCAT, TEXTJOIN, IFS, SWITCH, DGET, UNIQUE, FILTER, etc.
  • Nested Conditions/Customize Formulas*

Module 4:- Data Analysis

  • Data Sorting
  • Data Filtering
  • Named Ranges
  • 10 different ways to use Conditional Formatting
  • 10 different use of Data Validation
  • What-If Analysis

Module 5:- Excel Charts

  • Introduction to Excel Charts
  • Exploring the most commonly used Charts and Templates
  • Basics of Charts
  • Selecting Requirement based Charts
  • Working with Basic Charts:
  • Creating Customized / Advanced Charts
  • Creating Dynamic Chart
  • Working with Dynamic Interactive Charts in Excel using Drop Down
  • Working with Chart Elements, Formatting, Chart Styles, Properties, etc.

Module 6:- Pivot Tables

  • Introduction to Pivot Table
  • Creating a Pivot Table
  • Use of Calculated Fields/Items
  • Pivot Table Formatting
  • Grouping Items & Summarizing data in Pivot Tables
  • Grouping and Bucketing data in Pivot Table
  • Changing/Modifying Data Sources
  • Working with Pivot Table Designs & Layouts
  • Exploring Important Pivot Table Options & Field Settings
  • Pivot Table Filters
  • Changing Pivot Table Summary Calculation
  • Use of Slicers in Pivot Table
  • Using Source Data to Convert into Infographic Summary
  • Introduction to Pivot Charts

Module 1:- Getting Started with My SQL

  • An Introduction and Overview of MySQL
  • Installation and GUI Tools
  • An Overview

Module 2:- My SQL Fundamentals

  • Introducing SELECT statement
  • Introducing WHERE clause
  • Sort result with ORDER BY
  • Using FROM to specify the source tables
  • Importance of Clause Orders
  • Data Modification tricks

Module 3:- Creating Database & Tables

  • Creating a database
  • Creating a table
  • Creating Indexes
  • Controlling column behavior with constraints
  • Using foreign key constraints
  • Creating an ID column
  • Changing a schema with ALTER
  • Introducing NULL and NOT_NULL
  • Introduction to MySQL Data Types
  • Setting up default values
  • MySQL Warnings
  • Alerting a table

Module 4:- My SQL Functions & Clause

  • Introduction to MySQL Functions
  • Aggregate Functions – COUNT, MIN, MAX, SUM, AVG, ROUND etc
  • Control Flow Functions – IF, IFNULL, NULLIF etc.

Module 5:- Multiple Tables & Joins

  • Introduction to JOINS
  • Different types of JOINS
  • JOINS and Aliases
  • Multiple Table Joins
  • Creating a simple Subselect
  • Understanding of Primary keys and Foreign keys

Module 6:- Transactions, Stored Routines & Triggers

  • Transactions & Stored Routines
  • Triggers

Bonus Modules

  • Creating a New User Login
  • Granting access to new users
  • Backup and Restore databases
  • Important Keyboard Shortcuts Guide
  • Session Study Material
  • Situational Case Studies for Best Practice and Getting Ready for Corporate World
  • 6 Months Live Support via Phone/Email/Messages

Module 1:- Getting Started with Tableau

  • Introduction to Data Visualization
  • Leading Data Visualization Tools
  • Introduction to Tableau
  • Exploring Interface and Important Key Component
  • Navigating Through Tableau Menu Tabs
  • Exploring Each Menu Tab i.e. File, Data, Worksheet, Dashboard, Story, Analysis, Map, Format, Server etc.*
  • Tableau – Design Flow
  • File Types
  • Tableau Data Types
  • Show Me
  • Data Terminology

Module 2:- Connecting to Data with Tableau Desktop

  • Introduction to Data Connection
  • Data Source Interface
  • Types of Data Connections
  • Extracting Data
  • Custom Data View
  • Joins and Unions
  • Data Blending
  • Live Connection Vs Extract
  • Field Operations
  • Basic Project Activity

Module 3:- Examining & Filtering

  • The Sheet Interface
  • Dimensions & Measures
  • Hierarchies
  • Data Granularity
  • Highlighting
  • Data Sorting
  • Grouping Data
  • Data Filtering
  • Data Source Filters
  • The Filter Shelf
  • Dimension Filters & Card Modes
  • Context Filters
  • Measure Filters
  • Creating Sets

Module 4:- Field Types & Charts

  • Utilize Auto-Generated Fields
  • Use Titles, Captions and Tooltips Effectively
  • Creating Bins
  • ToolTip
  • Basic Charts

Module 5:- Calculations in Tableau

  • What are Calculations
  • Methods to Create Calculated Field
  • Introduction to Tableau Functions
  • Operator and Syntax Conventions
  • Introduction to Table Calculations

Module 6:- Level of Detail (LOD) Expression

  • Level of Detail (LOD) Calculations
  • Live Use Cases of LOD
  • Introduction to Parameters
  • Parameters Data Type Options

Module 7:- Geographical Visualization

  • Introduction to Geographic Visualizations
  • Assigning Geographical Locations
  • Spatial Files
  • Map Types
  • Custom Geocoding
  • Background Image

Module 8:- Advanced Charts in Tableau

  • Introduction to Advanced Charts
  • Bar in Bar Chart
  • Bullet Chart
  • Pareto Chart
  • Gantt Chart
  • Hierarchy and Tree Maps
  • Box and Whisker’s Plot
  • Waterfall Chart
  • Step and Jump Lines
  • Maps on a Scatter Plot
  • Bubble Chart
  • Control Chart
  • Funnel Chart
  • Packaged Bubbles
  • Word Cloud
  • Donut Chart
  • Trendlines
  • Reference Line, Bands, and Distributions

Module 9:- Dashboard & Stories

  • Introduction to Dashboards
  • The Dashboard Interface
  • Important Dashboard Objects
  • Adding Objects to the Dashboard
  • Building a Dashboard
  • Dashboard Design and Formatting
  • Types of Actions
  • Designing Dashboard for Tablets & Mobile-Phones
  • Story Points
  • Sharing Workbook
  • Wrapping up Tableau Program

Module 1:- Introduction to Power BI

  • What is Data Analytics & Data Visualization
    • Introduction to Data Analysis
    • Introduction to Data Visualization
    • What is Business Intelligence?
    • Overview of Self-Service Business Intelligence (SSBI) Tools
    • Leading Self-service tools
    • Comparison of Leading Visualization Tools
  • Getting Started with Power BI
    • Introduction to Microsoft Power BI
    • Why Power BI
    • Power BI Elements
    • Basic Components of Power BI
    • Building Blocks of Power BI
    • Key Benefits of Power BI
  • Hands-On
    • Power BI Installation
  • Skills Gained
    • Understanding of Data Analysis & Visualizations
    • Concepts of Business Intelligence
    • Installing Power BI on the System
    • Elements and Building Blocks of Power BI

Module 2:- Getting Data from Different Data Sources

  • Power Bi Desktop (Getting Data)
    • What is Power BI Desktop
    • Quick Walk-through Power BI Interface
    • Views in Power BI Desktop
    • Report View
    • Data view
    • Model view
    • Understanding ETL Concepts: Extract, Transform & Load
    • Data Sources in Power BI Desktop
    • Connecting and Getting data from different sources in Power BI
    • Getting data from Excel, CSV, Access, etc
    • Saving Workfile
  • Hands-On
    • Identifying and retrieving data from different data sources
    • Extracting and Loading data into Power BI
    • Preparing Data
  • Skills Gained
    • Concepts of ETL tool
    • Getting data from multiple sources

Module 3:- Clean, Transform and Load the Data

  • Shaping Data using Power Query
    • Loading data into Power BI Desktop
    • What is Query Editor
      • Cleaning Data with Query Editor
    • Transforming Data with Query Editor
      • Unpivoting Columns
      • Eliminating Rows / Columns
      • Changing / Modifying Data Types
      • Adding Custom Columns
      • Replacing Values / NULL
      • Promoting / Demoting Row as Header
      • Modifying and managing existing ‘Steps’
    • Extracting Date Components from Date-Time
    • Introduction to “M Query”
    • Combining Data
      • Append Merge / Joins, Transpose & Formatting Data Operations
    • Hands-On
      • Cleaning Data using Power Query Editor
      • Shaping the data
      • Transforming and cleaning the data
      • Merging Rows / Columns from multiple tables
      • Joins / Append activities
    • Skills Gained
      • Data Transformation using Query Editor
      • Loading the data
      • Understanding of “M Query”

Module 4:- Design a Data Model

  • Introduction to Data Modeling
    • Understanding of Relationship
      • What is Relationship?
      • One to Many Vs One to One Relationship
    • Auto-Detect Relationship during Load
    • Dimension Table Vs Fact Table
    • Cardinality in Data Modeling
    • Creating Relationship Manually
    • Managing Data Relationship
    • Editing Relationship
    • Creating Calculated Columns
    • Creating Measures
    • Optimizing Data Models for Better Visuals
    • Cross Filter Direction
    • Defining Hierarchies
  • Hands-On
    • Creating Model Relationships
    • Managing Relationships
    • Creating Measures
    • Creating hierarchies
  • Skills Gained
    • Understanding the basics of data modeling
    • Defining relationships and their cardinality
    • Understand star schema and its’ importance
    • Managing relationships

Module 5:- DAX Formulas & Calculations

  • Introduction to Data Analysis Expression (DAX)
    • Importance of DAX
    • Data Types in DAX
    • Defining Calculation Type
      • Calculated Column Vs Calculated Measures
      • Adding New Measures to Report
      • Creating Calculated / DAX Tables
    • DAX Syntax & Operators
    • Most Important & Common Basics & Advanced DAX Functions
      • Aggregate Functions
      • Logical Functions
      • Time-Intelligence Functions
      • Information Functions
    • DAX Variables
    • Formatting DAX Code
    • Handling Errors in DAX Expressions
  • Hands-On
    • Creating Calculated Tables
    • Creating Calculated Columns and Measures
    • Writing DAX calculations to perform Data Analysis
    • Beautifying DAX
    • Creating Variables
  • Skills Gained
    • Understanding DAX
    • Create Calculated Columns, Measures & Tables
    • Working with Advanced functions e.g. Time-Intelligence, Filter contexts etc.

Module 6:- Data Visualization & Creating Reports

  • Introduction to Visuals in Power BI
    • Creating Visualization
    • How to use Visual
    • Exploring Visualizations’ List
    • Exploring Most Common & Important Visualizations
      • Bar, Column, Line and Area Charts
      • Pie, Donut, and Gauge Charts
      • Single Number Cards and Multi Row Cards
      • Table & Matrix Visuals
      • Combo Chart, Funnel and Treemap Charts
      • Slicer, KPI and Custom Visuals
      • Map & Filled Map Visuals
    • Modifying Color Properties of Charts and Visuals
    • Shapes, Text Box, Buttons, and Images
    • Types of Filters
    • Slice and Dice Data in Power BI
    • Drilling-Up/Down
    • Understanding Custom Visuals & How to add them
    • Customizing Canvas
      • Setting up Canvas & Must Know Global Fonts
      • Page Layout & Formatting
    • Bookmarks in Power BI
    • Reports in Power BI
    • Conditionally formatting tables/matrixes
    • Activity: Creating Sales Report
  • Hands-On
    • Creating visual and charts
    • Designing a report
    • Managing visual fields and format properties
  • Skills Gained
    • Creating and selecting effective visualizations
    • Designing report page layout and Visual modification
    • Adding report navigation & basic functionalities
    • Creating visually stunning reports

Module 7:- Power BI Service and Managed Workspaces

  • Introduction to Power BI Service & Workspaces
  • What is Power BI Service
    • Exploring Interface of Power BI Service
    • Understanding the Admin Portal settings
  • What is Power BI Workspace
    • Understanding of “Workspace”
    • My Workspace Vs New Workspace
    • Creating New Workspace
    • Sharing and Managing Workspaces
  • Roles in workspaces in Power BI
  • Exploring Power BI Licensing
    • Power BI Free Vs Power BI Pro Vs Premium
  • Hands-On
    • Publishing reports on Power BI Service
    • Creating workspaces
    • Sharing and Managing Reports
    • Moving important assets to App and Publishing app in Power BI
  • Skills Gained
    • Knowledge of Power BI Service (Cloud)
    • Workspaces in Power BI
    • Creating and managing a workspace

Module 8:- Creating Dashboard in Power BI

  • Dashboard in Power BI
    • Introduction to Dashboard
    • Difference between Report Vs Dashboard
    • Preparing and Creating Dashboard
      • Configuring a Dashboard
      • Pinning Visuals to Dashboard
    • Dashboard Tiles
      • Pinning Tiles
    • Dashboard Widgets
    • Introduction to Power BI Q&A
      • Asking questions about data
      • Fetching results using Q&A
      • Using Q&A to create a dashboard tile
    • Quick Insights in Power BI
      • Data Analysis using Quick Insights
    • Sharing and Collaborating Dashboard with Business Users
  • Hands-On
    • Creating a Dashboard
    • Pinning visuals to Dashboard
    • Adding text/video widgets to Dashboard
    • Sharing and Moving Dashboard to distributed app
    • Use of Power BI Q&A to question your data
  • Skills Gained
    • Dashboard creation from report
    • Enhancing dashboard usability
    • Importance of Q&A and Quick Insights

Module 9:- Data Gateway, Security & Schedule Refresh

  • Report Security in Power BI
  • Introduction to Row-level Security (RLS)
    • Setting up and Enforcing Row-level security
    • Implementing Row-level security
  • Data Gateway & Report Scheduling
    • What is Data Gateway
    • Types of Gateway
      • On-premises data gateway (personal mode)
      • On-premises data gateway (standard mode)
    • Installing Data Gateway
    • Data Gateway System Requirement
    • Benefits of Data Gateway
    • Scheduled Refresh & Refreshing Data
    • Managing Data Source
      • Adding and removing a Data Source
    • Hands-On
      • Configuring & Implementing RLS
      • Managing datasets
      • Setting up On-Premise Data Gateway
      • Connecting Reports on Power BI Cloud with Local Data Files
      • Schedule dataset refresh
    • Skills Gained
      • Dashboard creation from report
      • Enhancing dashboard usability
      • Importance of Q&A and Quick Insights

Bonus Module:- In-Class Project

  • In-Class Project: Building Sales Report & Dashboard from Scratch
    • Extracting Data from the Local Source
    • Transforming Data using Power Query
      • Cleaning, Shaping and Preparing the data if necessary
    • Loading Data to Power BI Desktop
    • Building Data Model
    • Visual and Charts
    • Row-level Security
    • Publishing Reports
    • Power BI Service
    • Creating Dashboard
  • Hands-On
    • Analyzing Sales data
    • Derive conclusions from the patterns and trends shown in the visualization
  • Skills Gained
    • Report and Dashboard creation
    • Publishing, sharing and collaborating it with Business users

Module 1:- Getting Started With R

  • Introduction To R
  • Installation Setup
  • A quick guide to RStudio User Interface
  • RStudio's GUI3
  • Changing the appearance in RStudio
  • Installing packages in R and using the library
  • Development Environment Overview
  • Introduction to R basics
  • Building blocks of R
  • Core programming principles
  • Fundamentals of R

Module 2:- Programming with R

  • Creating an object
  • Data types in R
  • Coercion rules in R
  • Functions and arguments
  • Conditional Statements and Loops
  • if else, for, while, repeat, break, next

Module 3:- Objects in R

  • Vectors and Vector operation
  • List and Operations
  • Factor and Operations
  • Matrices
  • Data Frame
  • Applications of R objects
  • Data Inputs and Outputs with R
  • Advanced Visualization
  • Using the script vs. using the console

Module 4:- Manipulating Data

  • Data transformation with R
  • Dplyr package
  • Sampling data with the Dplyr package
  • Select, filter, arrange, rename
  • Mutate, pipeline
  • Group by, summarize

Module 5:- Start Visualizing Data

  • Intro To Data Visualization
  • Introduction To Ggplot2
  • Coloring, Filling Color, Axis, Legend, Labelling
  • Histogram, Density
  • Bar Chart, Point Plot
  • Box And Whiskers Plot, Outliers
  • Scatterplot
  • Pie Chart

Module 6:- Projects & Assignments

  • 2 Assignments
  • 1 Projects
  • Dataset Analysis

Please Note:- This tool will be at self-paced

Module 1: Getting Started with Python Core

✓ Need of Programming with an Example
✓ Why Programming
✓ Advantages of Programming
✓ Different Programming Languages
✓ Introduction to Python
❑ A Brief History of Python
❑ Why Python
✓ Installing Python
✓ Creating Python File using IDLE
✓ Write your first Program in Python
✓ How to execute Python Program
✓ Identifier
❑ Rules for Naming Identifiers
✓ Variables
✓ Operator
❑ Operator Types
✓ Q&A

Module 2: Datatypes in Python

✓ Introduction to Python Data Types
✓ Strings
❑ Introduction to Python ‘String’ data type
❑ String Properties
❑ String built-in functions
❑ Programming with Strings
❑ String Formatting
✓ Lists and Tuples
❑ Introduction to Python ‘List’ data type
❑ List Properties
❑ List built-in functions
❑ Programming with Lists
❑ List Comprehension
❑ Introduction to Python ‘tuple’ data types
❑ Tuples as Read only lists
✓ Dictionary and Sets
❑ Introduction to Python ‘Dictionary’ data type
❑ Creating a dictionary
❑ Dictionary built-in functions
❑ Introduction to Python ‘set’ data types
❑ Set and Set properties
❑ Set built-in functions
✓ Q&A

Module 3: Conditional & Control Statements in Python

✓ Introduction to Conditional Statements
❑ Types of Conditional Statements
o If….Statement
o If….Else Statement
o Elif…. Statement
✓ Introduction to Loops
❑ Types of Loops in Python
o While….Loop
o For….Loop
o Nested Loop
✓ Introduction to Loop Control Statements
❑ Loop Control Statements Keywords
o Break Statement
o Continue Statement
o Pass Statement
✓ Q&A

Module 4: Functions in Python

✓ Introduction to Python Functions
✓ User Defined Functions
❑ Functions definition and return statement
❑ Calling a Function
❑ Parameters and Arguments
❑ Required Arguments
❑ Default Argument
✓ Variable Scope in Function
❑ Local Scope
❑ Global Scope
❑ Enclosing Scope
❑ Built-in Scope
✓ Modules and Packages
❑ Importing Module (from, import statement)
✓ Anonymous functions (Lambda)
✓ Q&A

Module 5: Exception Handling & OOPs Concepts

✓ Getting started working with Files
❑ File Objects and Modes of file operations
❑ Reading, Writing, and use of ‘With’ Keyword
❑ Read(), Readline(), Readlines(), Write(), Writeline()
✓ Introduction to Exception Handling
❑ Understanding Exceptions
❑ Handling An Exceptions
❑ Try, Except, Else, and Finalizing
❑ Raising Exceptions with: Raise, Assert
✓ Introduction to Object Orientated Programming (OOPs)
❑ Why OOPs
❑ Difference Between POPs and OOPs
❑ OOPs Concepts
❑ Python OOP Vs Other OOPs
❑ Class and Objects
❑ Relation Between Class and Objects
❑ Creating a Class
❑ Attributes
✓ Built-In Class Attributes
✓ Class Variable and Instance Variable
❑ Constructor and Destructor
❑ Multiple Constructors
❑ Abstraction
❑ Inheritance
✓ Inheritance Types
❑ Overloading
❑ Overriding
❑ Data Hiding
✓ Q&A

Module 6: Database Connectivity & Regular Expressions

✓ Introduction to Regular Expressions
❑ What are Regular Expressions
❑ Regular Expressions Operations
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❑ Search Function
❑ Match Function
❑ Modifiers
❑ Patterns
✓ Database Connectivity
❑ Introduction to Database Connectivity
❑ Connections
❑ Executing Queries
❑ Transactions
✓ Q&A

Module 7: Data Manipulation & Data Visualization

✓ What is Data Manipulation
✓ Introductions to Pandas
✓ Data Manipulation with Pandas
✓ Data Structures & Series
✓ Data Frame
✓ Missing Values
✓ Data Operations
✓ Data Standardizations
✓ Pandas File Read (CSV, Excel, SQL) and Write Support
✓ Data Acquisition (Import & Export)
✓ Introduction to Data Visualization using Matplotlib
❑ Installing Matplotlib
❑ Plotting in Matplotlib
❑ Creating First Plot with Matplotlib
❑ Creating Column/Line/Scatter Plots
✓ Wrapping Python Core Program
✓ Q&


✔️ 98 Hrs – 100 Hrs / 50 Sessions
✔️ Per Session for 2 Hours
✔️ Practice Hours

We have included real-life examples and case studies in our course. Complete written notes and code for you to read and refer

Projects for you to complete throughout the course. These provide a challenge and an opportunity for you to apply your learning.

In a set of the time period, you will be having access to getting support from our expert

After completing your course, we will provide you with a Course Completion Certificate

You will get 100% job assistance according to your CTC, Experience and Present skills

Need more details about the course, let’s connect with our experts

Let’s Get Our Expert’s Guidance

    How, Data Science is having Best Career Opportunities?

    Skills in Demand

    Data science is a rapidly growing, highly sought-after career path for skilled professionals. To be successful in this field, data scientists must have more than just the traditional skills of analyzing large quantities of data and programming; they must also understand the entire data science life cycle and possess an adequate level of adaptability to maximize returns at each stage of the process.

    Employability Increases

    Companies are increasingly prioritizing candidates with strong skills in data science, specifically Python. Professionals who possess advanced knowledge of automation using Python, Machine Learning, Power BI, and Tableau are highly desirable as many organizations rely heavily on these programs for data analysis and visualization.

    Job opportunities on the rise

    Data Science has been ranked the top job on Glassdoor and boasts an impressive average salary of $120,000 in the United States according to Indeed! Data Science is a highly rewarding career path that enables one to solve some of the world’s most fascinating problems.

    Most Frequent Questions and Answers

    Those who are interested in Data Science and wants to start their career as Data Scientist. Anyone who is particularly interested in big data, machine learning, and data intelligence

    Of course, you can learn Python without having any coding background. We start Python learning from scratch so that we can build a strong fundamental of the application and at an advanced level you can grasp it easily. And obviously, you need a lot of practice to be a pro.

    Though we have so many reasons to join us, let us highlight the main points:-

    1. After completing the course you will get 3 months of support time period extra to revise the sessions which are not cleared to you, any problem you are not able to solve that you can take our team’s help
    2. We provide video recordings if any of the reason you skip your session
    3. We have well-experienced trainers to teach our students
    4. Project-based training / unlimited examples to make you understand about the subject / Case Studies after every session / Job Support and many more

    Yes, of course, you will be getting “Completion Certificate” 

    • Start at zero and become an expert whilst learning all about the inner workings of Python.
    • Learn how to write professional Python code like a professional Python developer.

    • Embrace simplicity and develop good programming habits.

    • Improve your Python code with formatters and linters

    • Extract information from existing websites using web scraping.

    • Learn to interact with REST APIs to fetch data from other web applications.

    Data Scientist has been ranked the number one job on Glassdoor and the average salary of a data scientist is over $120,000 in the United States according to Indeed! Data Science is a rewarding career that allows you to solve some of the world’s most interesting problems!

    Student Reviews

    Had great experience learning at ATH. Joined in January 2022 for 3 months program for Excel, My SQL and power BI....learned from Anil Sir and Nayan Sir...both great teachers...will definitely recommend all to join this program. Also, in job interview it helps when you are trained in multiple skills.
    Anubhav Mahajan
    Machine Learning Engineer

    I was struggling with advance excel when I find out about this platform and I decided to take Data Science course from here and my overall experience was quite amazing I am glad i found out about this platform in just few weeks i got to learn so much and I would recommend this to everyone.
    Dolly Bhardwaj
    Data Architect and Administrators
    Hi folks , i have completed my training part that is Data Science course with ATH in a budget . big thanks to Anil dhawan sir who helped me to clear every party MY sql , and also to Mr. Nayan who taught me POWER BI DESKTOP. At the end of training and hard work which i given to myself is endless. I am delighted to share that , I got placed with "KPMG" as a Business IT Analyst role.
    ATH student review
    Chandan Chauhan
    Business IT Analyst

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