Why Data Science?

  • Data Science will create 11.5 million jobs in India by 2026- IndiaTimes
  • Data science is one of the Top 10 fastest-growing jobs in tech industry - TOI
  • Hiring in the data science industry has increased by 46% Since 2019
  • There has been 39% rise in demand of Data Science Professionals
  • Average income of Data Scientists is around Rs. 6 to 9 LPA. Job ranking #3 among top Jobs in 2022

Data Science Roles

Data Science Manager
Data Scientist
Data Engineer
Data Analyst
Machine Learning Engineer
Business Intelligence Engineer

About InfiVidhya

We are a bootcamp company that provides upskilling programs for students and working professionals. We offer customizable pricing options and corporate training solutions to meet your specific needs. At Infividhya, we are dedicated to providing the best possible education and training to help you succeed in your career. Our expert instructors are passionate about their fields and are committed to helping you achieve your goals.

24*7 Support through WhatsApp, email, Calls

200+ Hrs of Learning & traning

Hands on sessions by industry mentors

400+ hrs of assignments & capstone projects

Key Features

Live-online Masterclasses delivered by Google, Amazon, Oracle and SAP experts

25+ years experienced instructors in the field of Data Science

Top-notch curriculum with integrated labs

Personalized Dashboard

6 Month Offline Program

Capstone Projects and free industry internship

TOOLS
Data Science
Learning path

Course and Internship Certificate

1. Job Assistance

2. Internship and Capstone Projects

3. Offline Learning and Training

Program Outcome

  • A solid understanding of fundamental data science concepts, techniques, and methodologies.
  • Enhance programming skills and teach how to leverage programming tools and libraries to handle data and build models.
  • Gain practical skills in data handling, cleaning, preprocessing, and analysis.
  • Ability to work on real-world datasets, define problem statements, develop and implement data-driven solutions, and evaluate the performance of their models.
  • Ability to think critically, analyze data effectively, and make data-driven decisions
  • effectively communicate their findings and insights to non-technical stakeholders.
  • Developing problem-solving abilities.
  • Hands-on experience with real-world projects.
  • Enhancing communication and teamwork skills.

Syllabus

  • Definition and overview of Data Science
  • Importance and relevance of Data Science in today's world
  • Applications and impact of Data Science in various industries
  • Role of Data Scientists and the skills they possess

  • Basic Excel functionalities for data analysis
  • Using formulas in Excel
  • Lookup and merging data in Excel
  • Data validation and decision-making functions in Excel
  • Working with nested IF statements/li>
  • Using advanced functions like INDEX, MATCH, and XLOOKUP
  • Data preparation techniques in Excel
  • Creating PivotTables and summarizing data
  • Visualizing data with charts and dashboards in Excel
  • Forecasting and business analytics in Excel

  • Introduction to MySQL and database concepts
  • Database design and normalization
  • Entity-Relationship Diagram (ERD) modeling
  • Creating databases and tables in MySQL
  • SQL querying and data manipulation in MySQL
  • Working with advanced SQL operations and functions
  • Joining tables and using views in SQL
  • Introduction to advanced SQL concepts
  • Data warehousing and ETL pipelines
  • Cloud-based data warehousing solutions
  • Introduction to Azure Data Factory and Azure Data Storage

  • Introduction to Power BI and its components
  • Connecting to data sources in Power BI Desktop
  • Data transformation and cleaning using Query Editor
  • Data modeling and creating relationships in Power BI
  • Advanced data manipulation with M Query
  • Introduction to DAX (Data Analysis Expressions)
  • Creating interactive reports and visualizations in Power BI
  • Applying filters and slicers for data exploration
  • Creating dashboards and publishing reports in Power BI Service
  • Advanced data visualization techniques in Power BI
  • Power BI report service basics and web portal usage
    • .

  • Introduction to Python programming language
  • Python basics and data types
  • Control statements and loops in Python
  • Data structures in Python (strings, lists, tuples, sets, dictionaries)
  • Functions and iterators in Python
  • Introduction to NumPy for numerical computing
  • Introduction to Pandas for data manipulation and analysis
  • Data visualization with Matplotlib in Python
  • Exploratory data analysis (EDA) techniques in Python
  • Handling missing values and outliers in Python

  • Introduction to statistics and its importance in data science
  • Descriptive statistics and measures of central tendency
  • Measures of dispersion and quartiles
  • Correlation and covariance analysis
  • Probability theory and distributions (uniform, Gaussian, binomial, etc.)
  • Central limit theorem and hypothesis testing
  • Parametric and non-parametric tests
  • Statistical inference and confidence intervals
  • Introduction to linear algebra for data science applications

  • Introduction to machine learning and its applications
  • Supervised vs unsupervised learning
  • Linear regression and logistic regression
  • K-nearest neighbors (KNN) algorithm
  • K-means clustering for unsupervised learning
  • Principal component analysis (PCA) for dimensionality reduction
  • Decision tree and random forest algorithms
  • Naive Bayes classifier
  • Gradient boosting and XGBoost
  • Support Vector Machines (SVM)
  • Introduction to artificial neural networks (ANN) and deep learning

  • Introduction to time series data and its characteristics
  • Trend, seasonality, and cyclical patterns in time series
  • Autoregressive integrated moving average (ARIMA) models
  • Autocorrelation and partial autocorrelation analysis
  • Time series decomposition and forecasting techniques
  • Evaluation and validation of time series models
  • Advanced time series forecasting models and techniques

  • Data Science Internship

Mock Interviews & Career Counselling

Personality Development

  • Self-awareness
  • Self-esteem and self-confidence
  • Emotional intelligence
  • Communication skills
  • Interpersonal skills
  • Leadership skills
  • Positive thinking and optimism
  • Personal branding

Mock Interviews

  • Personal Introduction
  • Behavioral Questions
  • Technical Questions
  • Job-Specific Questions
  • Situational Questions
  • Cultural Fit and Values
  • Strengths and Weaknesses
  • Career Goals and Motivation

Resume Building

  • Start with the Basics
  • Review Resume Formats
  • Analyze Job Descriptions
  • Highlight Key Components
  • Showcase Transferable Skills
  • Review Proofreading
  • Provide Continuous Support
  • Linkedin Profile Building

Mentors

Jimit Rangras

Senior Solutions Consultant,

Google, Chicago, US

Rasesh Saraiya

Frontend Engineer II

Amazon

Yeshu Pandit

Senior Application Developer

Oracle

Ashish Singh

Software Developer,

Ex Amazon , SAPS Labs

Capstone Projects

Article Recommendation system

Demand forecast for Food items

Healthcare

Sales Prediction

Review Analysis System

Hate Speech Classification

Loan approval automation System

Classification of Emergency vehicles during emergency situation

Contact Us

6351377405

contact@infividhya.com