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Full Stack Data Science: Course, Fees, Duration, Online

Course

Lipi Kaushik

Updated on 26th December, 2023 , 3 min read

Full Stack is the skill that one needs to get a project done by considering every component as a stack. One who is interested in working as a Full Stack Data Scientist should know that they shoulder the responsibility of finishing the project started from scratch. Furthermore, who is interested in studying the course of Full Stack Data Science should know that there are various certification courses available at several institutes. 

One of the colleges that offer Full Stack Data Science courses is AlmaBetter. Moreover, the topics that are included in this course are Getting Started with Python, Data Types in Python, Indexing & Slicing, In-built Functions and Methods, Conditional Statements, etc. After the candidate completes the course, he/ she will be able to get various jobs. Moreover, the Full Stack Data Science salary ranges from INR 8-25 LPA. There are several top recruiters in this field, such as Airbnb, LinkedIn, Google, Netflix, Microsoft, etc. To know more about the Full Stack Data Science Course, read the complete article below.

Full Stack Data Science: Eligibility

The eligibility of the course of Full Stack Development is mentioned below: -

  • The candidate must have a working knowledge of technology and AI.
  • One must be skilled in not only Maths, but also databases, computer science fundamentals, etc.

Full Stack Data Science: Why to Study

There are several advantages to taking a Full Stack Development course, including learning the abilities and information required to become skilled in front-end and back-end development. The following are strong arguments in favor of taking a course in full stack development: -

  • Versatility and Full-Stack Proficiency

Front-end and back-end technologies are thoroughly understood in Full Stack Development courses. Because of their adaptability, developers can work on any part of the web development stack, which increases their marketability.

  • Broader Career Opportunities

Due to their ability to manage a wide range of activities throughout the development process, Full Stack Developers are in high demand. Their adaptability increases their overall employment options by making them eligible for roles in startups, small businesses, and major corporations.

  • End-to-End Project Understanding

Students who enrol in Full Stack Development courses learn how to work on all facets of web development projects. The development process is comprehensively understood by students, who learn everything from creating user interfaces to putting server-side logic and database management into practice.

Full Stack Development: Admission

The aspirants who want to take admission in the course of Full Stack Development will have to follow a certain procedure. Moreover, the admission procedure varies from institute to institute. To get enrolled into the course, one should follow the process mentioned below: -

  • Go to the official website of the institute you want to get enrolled in.
  • Click on the link of the enrolment.
  • Fill in all the necessary details in the form.
  • Pay the registration fee.
  • Download and save the enrolment receipt for future purposes.

Full Stack Development: Syllabus

The syllabus in the course of Full Stack Development can be found in the table below: -

Topics

Syllabus

Introduction to Computer Programming

  • Getting Started with Python
  • Data Types in Python
  • Indexing & Slicing
  • In-built Functions and Methods
  • Conditional Statements
  • Loops & Iterations
  • Conditional & Infinite Looping
  • Advanced Looping Concepts
  • Custom functions in Python
  • Lambda & Map Functions
  • Errors and Exception Handling
  • OOPs in Python
  • Coding Best Practices
  • Arrays and Strings
  • Recursion - I and II
  • Sorting Algorithms
  • Search Algorithms
  • Competitive Coding

Numerical Programming in Python

  • Packages & Libraries - OS
  • Datetime, Regex & Beautiful Soup
  • Command Line & File System
  • Git and Github
  • Standard Data Management Libraries
  • Data Wrangling using Pandas and Numpy
  • Data Visualisation Libraries - Matplotlib & Seaborn
  • Exploratory Data Analysis

Relational Databases

  • Getting Started with SQL
  • SQL Environment & Basic Commands
  • Fundamentals of SQL Query
  • Dealing with Multiple Tables
  • Advanced SQL Joins
  • Mathematical & Data type conversion Functions
  • DateTime & String Functions
  • Window Functions
  • Miscellaneous Functions
  • Connect & Analyse Data with SQL & Python
  • Database Management & Schema Design
  • Competitive Coding & Query Optimisation
  • Complex queries using CTE & Pivoting
  • Type Casting & Math Functions
  • Advanced SQL Joins
  • Type Casting & Math Functions

Data Visualisation Tools

  • Fundamentals of Excel
  • Data Exploration with In-Built Functions
  • Storytelling with Excel
  • Advanced Dashboarding Concepts - Macros & VBA
  • Getting Started with Tableau Ecosystem
  • Choosing the Right Chart - Visual Intuition
  • Storytelling with Tableau
  • Intro to Power BI
  • Intro to Google Analytics
  • Dashboarding and SQL

Applied Statistics

  • Calculus for ML
  • Vector Algebra
  • Matrix Algebra
  • Probability Theory
  • Data Summarization
  • Probability Distributions - Discrete and Continuous
  • Joint Distribution
  • Sampling and Statistical Inference
  • Concept of Confidence
  • Hypothesis Testing
  • Statistical Inference in Industry - A/B testing

Introduction to Machine Learning

  • Getting Started With ML
  • ML Lifecycle
  • Implementing simple Supervised Algorithm
  • Linear & Tree based models
  • Implementing simple Unsupervised Algorithm
  • Unsupervised Clustering: K-means & Hierarchical
  • Data Preparation for ML Models
  • Cross validation
  • Hyperparameter tuning
  • TedX Views Prediction - Case Study
  • Customer Segmentation - Case Study
  • Time Series Analysis
  • Bagging & Boosting: Complex Algorithms
  • Nonlinear Algorithms - Polynomial Regression
  • SVM & Neural Networks
  • Natural Language Processing
  • Image processing
  • Recommender Systems
  • SQL Feature Engineering, Prediction and Analysis

Distributed Machine Learning

  • Big Data Fundamentals
  • Data Warehousing with Hive
  • Apache Spark using Python
  • Distributed ML Training

Product Analytics

  • Product Analytics Essentials
  • Core Visualisation Principles
  • Product Intelligence Platforms
  • Advanced Query Optimisation
  • Business Process Automation

Deep Learning

  • Deep Neural Networks
  • Natural Language Processing
  • Computer Vision

Full Stack Development: Jobs

After the completion of the course of Full Stack Development, one can find the 

  • Full Stack Developer
  • Front-End Developer
  • Back-End Developer
  • UI/UX Developer or Designer
  • Software Engineer
  • Technical Lead
  • DevOps Engineer
  • Entrepreneur/Startup Founder
  • Systems Analyst
  • Freelancer/Contractor
  • E-commerce Developer
  • Educator/Trainer

Full Stack Development: Salary

The salary in this field varies from INR 8-25 LPA. Moreover, the salary depends on several factors such as the skills of the candidate, qualifications, etc.

Frequently Asked Questions

What is Full Stack Data Science course

Ans. The ability to complete a project by treating each component as a stack is known as full stack. If someone is interested in a career as a Full Stack Data Scientist, they should be aware that the job must be completed from start to finish.

What are Full Stack Data Science colleges in India

Ans. The Full Stack Data Science course is offered in various institutes in India. However, one of the institutes serving this course is AlmaBetter.

Which is better full stack or data science

Ans. Whether you want to work as a full-stack developer or a data scientist, these are both in-demand careers. Both present a wealth of options. Data science is the route to go if you are interested in working with and analysing data. If web development is your thing, then full-stack development is the way to go.

What is stack in data science

Ans. The top of a stack data structure is where insertion and deletion operations are permitted. Stacks are a linear form of data structure that adheres to the LIFO (Last-In-First-Out) principle.

How much do full stack data scientists make

Ans. The salary of a full stack scientist vary from INR 8-25 LPA.

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