Learn Data Science and analyze massive data sets
Build in-demand tech skills
Create a job-ready portfolio
Get hired as a data scientist
This program is offered in partnership with Knowledgehut by upGrad, a global leader in higher online education with 2 million learners across 100 countries worldwide. With the latest technology, pedagogy, industry partners and world-class faculty, upGrad creates immersive online learning experiences for learners globally.
Data scientists are among the most in-demand professionals across the spectrum of industries because of their unique ability to make sense of big data, draw insights from it, and helping businesses leverage those insights to drive profitability. Most importantly, data scientists use such insights to solve the everyday problems and make the world a better place.
The KnowledgeHut Data Science Bootcamp has foundational and advanced phases of learning with plenty of projects for you to hone skills that you acquire during classroom lessons. By the end of the Bootcamp, you are well placed to show off your analytics, ML, and applied data science expertise to open doors for opportunities at Tier 1 companies and more!.
Learning Objectives:
Get introduced to the fundamentals of MS Excel along with the formatting concepts and formulas and Statistical Analysis using Excel.
Topics:
- Formatting Concepts
- Formulas in Excel
- Statistical Analysis
- Introduction to Other Features
Learning Objective:
- Learn how to install Python distribution – Anaconda. Learn basic data types, strings & regular expressions.
Topics
- What is Code and Data
- Creating Data
- Using Data with Code
- Syntax and Naming Conventions
Learning Objectives:
Understand the fundamental concept of a database and learn how a Relational Database stores data. Learn to perform advanced data analysis by mastering SQL.
Topics:
- What is SQL and Why is it Important?
- SQL Database Admin Commands
- The Basics of SQL Query
- Filtering Data Using WHERE Clause in SQL
- Aggregation and Summary Functions in SQL
Learning Objectives:
Learn the basics of storing, manipulating, and retrieving data stored in a relational database to advance analysis of data making efficient analysis.
Topics:
- Miscellaneous Analysis in SQL
- Table to Table Relationship in SQL
- Combining Tables
- Advanced SQL Data Analysis
- Making Efficient Analysis
Learning Objectives:
Master Python, starting with the fundamentals and go on to understand different data types and data structures. Learn flow control, how to use predefined functions and how to handle errors. Understand basic and advanced visualizations using Matplotlib, Seaborn and Plotly.
Topics:
- Installation and Set Up
- Code and Data
- Building Blocks
- Strings
- Data Structures
- Flow Control
Learning Objectives:
Understand how to perform outlier analysis, learn Lambda functions and OOPs and how to scrape data.
Topics:
- Functions
- Modules
- Files
- Lambda functions, Error, and Exception Handling
- OOPs
Learning Objectives:
Learn the concepts of probability and statistics including essential concepts like hypothesis and regressions. Master how to process raw data to get it ready for another data processing operation.
Topics:
- Measures of Central Tendencies and Dispersion – (Mean, Median and Mode), (Variance,
- Standard Deviation, IQR, Skewness and Kurtosis)
- Distributions – Normal Distribution and Standard Normal Distribution, z-Scores
- Probability Theory – Simple Probability, Rule of Addition and Multiplication, Bayes
- Theorem and Law of Large Numbers
- Central Limit Theorem
- Binomial and Poisson Distributions
Learning Objectives:
Learn how to test hypotheses and the meaning of Type1 and Type2 errors. Understand the ins and outs of ANOVA and regression analysis.
Topics:
- Hypothesis Testing – Intro to Hypothesis, H0, H1, Significance and P-value
- Type1 and Type 2 errors, Confidence Intervals, Margin of Error
- z-test and t-test
- Regressions
- ANOVA
Learning Objectives:
Perform exploratory data analysis using NumPy and Pandas and learn all about RegEx and data visualizations.
Topics:
- Numpy
- Pandas
- Regular Expressions
- Visualization
Learning Objectives:
Learn how to scrape websites with Python and learn what a clear version of “EDA” means and entails.
Topics:
- Web Scraping
- EDA
Topics
- Introduction to Pandas
- Reading various file formats
- Creating Pandas Series and DataFrames
- Series Operations
- DataFrame Operations part 1
- DataFrame Operations part 2
Topics:
- Introduction to RegEx
- Meta characters (part 1)
- Meta characters (part 2)
- Special sequences (part 1)
- Special sequences (part 2)
Topics:
- Introduction to Visualization
- Basic plots
- Sub plots
- Bar, Pie, Histogram and Scatter
- Plots using Pandas
Topics:
- The concept of class and an object
- Python class, methods, members, objects
- Concept of __init__
- Updating values using methods
- Encapsulation
- Inheritance
Topics:
- Various types of files
- Recap of CSV files with pandas
- SAS Files
- STATA Files
- HDF5 Files
- JSON Files
- YAML Files
- Various databases
- Connection and Cursor Objects
- Reading Data
- Creating Databases and Tables
- Insert Data
- Update & Delete Data
- Other Databases
Programming: Knowledge of programming fundamentals is good to have, but not mandatory.
Mathematics: Basic knowledge of programming and high-school level math (functions, derivatives, systems of linear equations) is beneficial, though not mandatory.
Logical Thinking: The right aptitude, logical thinking, and drive for curiosity are all you need—leave the rest to us!.
Beginner Data Scientists, Database Administrators, Business Analysts, Python Developers, Applications Architects, Data Analysts,
Data and Analytics Professionals, Product Managers, Graduates from any discipline, Professionals looking for a career change, Statisticians, Professionals looking to break into tech
After finishing the course Data Science Bootcamp at KnowledgeHut, you will receive a data science bootcamp certification of completion issued by KnowledgeHut. This certificate holds great significance as it is validated by prominent tech industry employers who actively contribute to the best data scientist bootcamp curriculum and collaborate with KnowledgeHut for the best bootcamp data science for their workforce training needs.
Additionally, choosing the blended learning option offers you the opportunity to obtain a certificate from Golden Gate University, California. This credential can greatly enhance your profile during the data science bootcamp job placement
By the end of this 31-week immersive learning bootcamp program, you will be able to face real-world Data Science problems and come up with the most appropriate solution with the skills to explore, clean, analyze and predict data.
In particular, you will build the skills to:
-Perform Data Analysis using tools such as Python, SQL, and Tableau
-Extract data perform Data Analysis to get meaningful insights
-Apply modeling and data analysis to find solutions to business problems
-Build the ability to present results using data visualization techniques
-Master statistical data analysis techniques utilized in decision making
-Apply Machine Learning Algorithms to help Businesses make predictions
-Use data mining techniques to get insights to solve real-world problems
-Use different Deep Learning frameworks to build real-world AI applications
-Use Natural Language Processing to build Chatbots and Sentiment Analysis
Along the way, you’ll put together a compelling professional-grade project portfolio that you can showcase to potential employers and collaborators. Complete the course and acquire job-ready tech skills to land a job as a Data Scientist.
