Upskill & Transition to Data Science Role

8 months live structured program designed by industry experts to upskill & successfully transition to Data Science roles.

Next batch starts on February

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From This Program, You Will Gain

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All the Right Skills required to transition to Data Science roles

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Multiple Industry-Relevant Projects to showcase in your resume

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Career transition to top-tier Data-driven companies

Past Alumni Achieving Dream Career Switches

Pulkit Gupta

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Bosscoder Academy's personalized onboarding, live classes, mentor sessions, and off-class support helped me to get an amazing hike. Personal attention assured me that the decision was worthwhile.

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Rohal Kurup

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Dreaming of a product-based company, I joined Bosscoder Academy. Their excellent curriculum and structured topics of Machine Learning guided me effectively rather than searching randomly on YouTube.

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Dream Career Switch Made Possible By:

Personalized Learning

Success Manager Ensures Personal Growth

Structured Curriculum

Covers all Concepts in Depth

Live classes by Top Data Scientists

Interactive Classroom with 4 Classes a Week

Regular 1:1 Mentorship Sessions

A Personal Mentor will be Assigned

Motivated Community

Learn with Like-minded Community

Recruitment Team

Get Diverse Placement Opportunities

Placement Support To Line Up Interviews

Profile Building

  • Resume Creation

  • LinkedIn Profile Optimization

  • Profile creation on other platforms

Interview Acing

  • Mock Interviews with expert mentors

  • Offline & Online Interview Preparation

  • Salary & Role Negotiation

Apply Right way

  • Opportunities in 250+ Partner companies

  • Referrals to almost all top product companies

  • Sharing hiring opportunities of different companies

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For every Bosscoder program enrollment, we contribute 1% towards the education of 'out of school' children.

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Structured Curriculum for a smooth transition to Data Science Roles

MODULE 1 - DATA FUNDAMENTALS ( BEGINNER )

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Duration: 8 Weeks

The first step towards becoming a Data Analyst, Data Scientist, or ML Engineer is to have strong command over the fundamentals of visualization, dashboarding & reporting of data.

Within this module, our goal is to become confident in data fundamentals.

Topics that will be covered:

1. Excel

  • Introduction to Excel and Formulas
  • Pivot Tables, Charts and Statistical functions
  • Google spreadsheets

2. Tableau + Excel

  • Flowcharts, Data Types, Operations
  • Conditional Statements & Loops
  • Functions
  • Strings
  • In-build Data Structures - List, Tuples, Dictionary, Set
  • Pivot Tables, Charts & Statistical functions
  • Matrix Algebra, Number Systems

3. SQL

  • Visual Analytics
  • Charts, Graphs, Operations on Data & Calculations in Tableau/ PowerBI
  • Advanced Visual Analytics & Level of Detail (LOD) Expressions
  • Geographic Visualizations, Advanced Charts, and Worksheet & Workbook Formatting
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USPs of our Delivery

  • All topics taught in live classes with limited batch size helping in instant doubt support to accelerate learning
  • Assignment (post-lecture) & their evaluation
  • Hyper-Personalied: Special focus on the individual with a constant touch from student success manager & mentor.

MODULE 2 - ANALYTICAL PROFICIENCY AND BUSINESS INSIGHTS ( INTERMEDIATE )

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Duration: 6 Weeks

As a Data Scientist, it is important we know how to break down business situations and design correct metrics.

Moreover, you should also be able to use the powerful language of SQL to extract and analyze data.

Within this module, our aim is for you to become skilled at interpreting data to make informed business decisions and to present your findings with clarity.

Topics that will be covered:

1. SQL

  • Introduction to Databases & BigQuery Setup
  • Extracting data using SQL
  • Functions, Filtering & Subqueries Joins
  • Joins
  • GROUP BY & Aggregation
  • Window Functions
  • Date and Time Functions & CTEs
  • Indexes & Partitioning

2. Product Analytics

  • Framework to address product sense questions
  • Diagnostics
  • Metrics, KPI
  • Product Design & Development
  • Guesstimates
  • Product Cases from Netflix, Stripe, Instagram
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USPs of our Delivery

  • Hyper-personalization: Depending on student-specific learning pace, multiple revision classes are organized
  • Assignments (post-lecture) & their immediate evaluation help to compare your performance against peers
  • The focus is not just to remember maths formulas but to help learners visualize the intuition behind concepts, enabling them to identify patterns
  • As you work on different business situation & product thinking, you gain a deeper understanding on what insights are important & what insights are not important for a particular scenario.

MODULE 3 - FOUNDATION OF MACHINE LEARNING & DEEP LEARNING ( ADVANCED )

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Duration: 10 Weeks

Mathematics is the foundation upon which Machine Learning & Deep Learning algorithms are built.

That is why, in this module, you will fall in love with mathematics as you solve engaging problems & build your solid foundations of Machine Learning & Deep Learning.

Advanced Python & Python Libraries:

1. Python Libraries

  • Python Refresher
  • Numpy, Pandas
  • Matplotlib
  • Seaborn
  • Data Acquisition
  • Web API & Web Scrapping
  • Beautifulsoup & Tweepy

2. Math for Machine learning

  • Basics of Time & Space Complexity
  • OOPS
  • Functional Programming
  • Exception Handling & Modules

Maths for Machine Learning:

1. Probability & Applied Statistics

  • Probability
  • Bayes Theorem
  • Distributions
  • Descriptive Statistics, outlier treatment
  • Confidence Interval
  • Central Limit Theorem
  • Hypothesis Test, AB Testing
  • ANOVA
  • Correlation
  • EDA, Feature Engineering, Missing value treatment
  • Experiment Design
  • Regex, NLTK, OpenCV

2. Calculus, Optimization & Linear Algebra

  • Classification
  • Hyperplane
  • Halfspace
  • Calculus
  • Optimization
  • Gradient Descent
  • Principal Component Analysis
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USPs of our Delivery

  • Hands-on Learning Experience
  • Learn maths from a case-study approach & Fall in love with Mathematics
  • Solve multiple real-life case study problems in live classes & understand the tradeoffs of each algorithm

MODULE 4 - SPECIALIZATION

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Duration: 8/18 Weeks

Within this module, you will work on multiple projects build in partnership with top companies.

You will get your hands dirty by working with messy & unclean datasets from real companies.

You have the flexibility to select either one or both of the offered specializations, based on your interests and career goals.

SPECIALIZATION 1: MACHINE LEARNING

1. Supervised Learning

  • MLE, MAP, Confidence Interval
  • Classification Metrics
  • Imbalanced Data
  • Decision Trees
  • Bagging
  • Naive Bayes
  • SVM

2. Unsupervised Learning & Recommender Systems

  • Introduction to Clustering, k-Means
  • K-means ++, Hierarchical
  • GMM
  • Anomaly/Outlier/Novelty Detection
  • PCA, t-SNE
  • Recommender Systems
  • Time Series Analysis

AND / OR

SPECIALIZATION 2: DEEP LEARNING ( 8 WEEKS )

1. Neural Networks

  • Perceptrons
  • Neural Networks
  • Hidden Layers
  • Tensorflow
  • Keras
  • Forward and Back Propagation
  • Multilayer Perceptrons (MLP)
  • Callbacks
  • Tensorboard
  • Optimization
  • Hyperparameter tuning

2. Computer Vision

  • Convolutional Neural Nets
  • Data Augmentation
  • Transfer Learning
  • CNN
  • CNN Hyperparameters Tuning & BackPropagation
  • CNN Visualization
  • Popular CNN Architecture - Alex, VGG, ResNet, Inception, EfficientNet, MobileNet
  • Object Segmentation, Localisation, & Detection
  • Generative Models, GANs
  • Attention Models
  • Siamese Networks
  • Advanced CV

3. Natural Language Processing

  • Text Processing & Representation
  • Tokenization, Stemming, Lemmatization
  • Vector space modeling, Cosine Similarity, Euclidean Distance
  • POS tagging, Dependency Parsing
  • Topic Modeling, Language Modeling
  • Embeddings
  • Recurrent Neural Nets
  • Information Extraction
  • LSTM
  • Attention
  • Named Entity Recognition
  • Transformers
  • HuggingFace
  • BERT
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USPs of our Delivery

  • Impactful projects like forecasting the exact number of orders to be placed at a restaurant on New Year’s Eve, or Forecasting the number of oxygen cylinders a hospital will require, and multiple others.
  • Hands-on experience with Machine Learning & Deep Learning algorithms
  • 1:1 discussion with your mentor regarding project improvements.

MODULE 5 - DATA SCIENCE IN PRODUCTION

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Duration: 8 Weeks

A great Data Scientist or ML Engineer is also capable of developing end-to-end pipelines & building applications powered by machine Learning models.

This is the reason why, Within this module, you will learn how to develop end-to-end ML pipelines. And you will work on the latest cloud platforms to deploy & monitor your models.

Moreover, Data structures & Algorithms are part of interviews at top product companies. That is why, you will also focus on Data Structures & Algorithms to be able to crack these interviews.

Topics that will be covered:

1. Machine Learning Ops

  • Streamlit
  • Flask
  • Containerisation, Docker
  • Experiment Tracking
  • MLFlow
  • CI/ CD
  • Github Actions
  • ML System Design
  • AWS Segemaker, AWS Data Wrangler, AWS Pipeline
  • Apache Spark
  • Spark ML lib

2. Advanced Data Structures & Algorithms

  • Arrays
  • Linked Lists
  • Stacks & Queues
  • Trees
  • Tries & Heaps
  • Searching & Sorting Algorithms
  • Recursion
  • Hashing & 2 pointers
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USPs of our Delivery

  • Impactful projects like forecasting the exact number of orders to be placed at a restaurant on New Year’s Eve, or Forecasting the number of oxygen cylinders a hospital will require, and multiple others.
  • Hands-on experience with Machine Learning & Deep Learning algorithms
  • 1:1 discussion with your mentor regarding project improvements.

MODULE 6 - GET PLACED AS DATA SCIENTIST AT TOP PRODUCT COMPANIES

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Duration: Until you get placed.

Once you have upskilled yourself to become a great data scientist, it is important that we now focus on getting you interview opportunities from diverse companies.

This process is usually of 3 phases:

  1. 1. Building a strong profile
  2. 2. Applying the right way
  3. 3. Acing the interview

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

Topics that will be covered:

1. Building a strong profile

  • Resume creation
  • LinkedIn Profile Optimization
  • Profile creation on other platforms

2. Applying the right way

  • Opportunities through Bosscoder collaboration with 100+ companies.
  • Referral to almost all top product companies.
  • Sharing hiring requirement of different companies.

3. Acing the interview

  • On Demand Mock Interviews
  • Offline and Online interview Guidelines
  • Salary Negotiation
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Outcome

You getting placed at one of the top tech companies like Google, Microsoft, Amazon, Apple & sharing us a personal review of your journey with us.

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USPs of our Delivery

  • Student success manager stay connected with you throughout your placement journey to ensure you achieve best outcome.
  • Collaboration with 100+ companies for tech hiring
  • Collaboration with consultancies who hire for top tech companies
  • Referrals from our alumni & mentor community for almost all the companies.
  • Resume reviews, profile building increasing your chances of getting shortlisted.
  • On demand mock interviews with mentor before a specific interview.
  • 100% support from our team to help you succeeds

Learn from Industry Veterans

Instructors & Mentors

Rated highly by Working Professionals Upskilling with us, these Instructors and Mentors are working in Top Tech Companies and are familiar with best ways to crack these companies.
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Megha Roy
Data Analyst - IV - Uber
SRM University alum with three years in data analytics. Experienced in creating Tableau dashboards, utilizing unsupervised learning algorithms, & focusing on anomaly detection and predictive learning.
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Manish Garg
Co-founder - Bosscoder
An IIT Dhanbad alumnus. From Samsung's Machine Learning engineer to collaborating with Android's founder at Essential and leading Quoori's speech department, his journey is remarkable.
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PARIJAT ROY
Senior Data Scientist - Microsoft
Seasoned data scientist from Microsoft with 8 years of industry experience. Parijat specializes in NLP for analyzing feedback and improving Net Promoter Scores for Office products.
Industry-Relevant  Projects
These projects are based on real-world scenarios and utilize datasets sourced from real companies.
#1
Email Categorization Tool
12 Hours
Microsoft is creating an email categorization tool to help users organize their inboxes. Use Python and machine learning (NLP) techniques to classify emails into predefined categories, SQL to store user feedback on categorization accuracy, and Tableau to visualize classification performance metrics
Python
SQL
Tableau
Machine Learning
NLP
#2
Network Utilization Dashboard for Infrastructure Planning
15 Hours
Jio requires a detailed analysis of network utilization for future infrastructure development. Pull network usage data with SQL, analyze the data for peak usage times using Python, and use Tableau to create a comprehensive dashboard for planners
Python
SQL
Tableau
certificate
Elevate Your Career with Bosscoder's Industry Recognized Certification
Tailored to improve your professional skills and unlock new career prospects.

Our Alumni Placed At

Bosscoder is a platform to

  1. 1. Upskill in Data Science concepts with Hands-on projects, using Datasets from real companies.
  2. 2. Get interview calls from data-driven product companies to make a successful career transition.

Still, have questions? Let our program specialist help you out!

Fee Structure

Total Fee : Rs. 1,59,000/- Rs. 1,27,200/-

With our affordable EMI option, your fee can be as low as Rs. 10,636/- month - that's even less than your monthly grocery bills.

Apply now

Next Batch starts on February

Are you a College Student, Working Professional or Graduated but not working? *