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 September
From This Program, You Will Gain
Solid command on fundamentals to advance concepts in Data Science
Proficiency in solving business case-studies & building real-life projects
Career transition to top-tier Data-driven companies
Past Alumni Achieving Dream Career Switches
Infosys
Hike
550%
Amazon
Working in Infosys, I was looking for a platform to prepare for interviews of product-based companies. Bosscoder’s structured program proved helpful.
Oracle
Hike
347%
Cisco
I was a beginner and could not be consistent in my preparation. Bosscoder Academy helped me grasp important concepts.
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
Mock Interviews
Understand your weak points
Have Machine Learning & Deep learning interviews
On-demand company-specific interviews
Right Opportunities
Opportunities In 100+ Partner Tech Companies
Referral to almost all top product companies
Sharing hiring opportunities of different companies
Structured Curriculum for a smooth transition to Data Analytics and Data Science Roles
Module 1 - DATA FUNDAMENTALS
Duration: 6 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. Beginner Python
- Flowcharts, Data Types, Operations
- Conditional Statements & Loops
- Functions
- Strings
- In-build Data Structures - List, Tuples, Dictionary, Set, Matrix Algebra, Number Systems
2. Tableau + Excel
- Basic Visual Analytics
- More Charts & Graphs, Operations on Data & Calculations in Tableau
- Advanced Visual Analytics & Level of Detail (LOD) Expressions
- Geographic Visualizations, Advanced Charts, and Worksheet & Workbook Formatting
- Introduction to Excel & Formulas
- Pivot Tables, Charts & Statistical functions
- Google Spreadsheets
3. SQL
- Introduction to Databases & BigQuery Setup
- Extracting data using SQL
- Functions, Filtering & Subqueries
- Joins
- GROUP BY & Aggregation
- Window Functions
- Date and Time Functions & CTEs
- Indexes & Partitioning
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 - DATA ANALYSIS AND VISUALIZATION
Duration: 6 Weeks
As a Data Analytics, Data Scientist, or ML Engineer, it is important we know how to break down business situations, design correct metrics & deal with uncertainty. Within this module, you will learn all of this.
Topics that will be covered:
1. Python libraries
- Numpy, Pandas
- Matplotlib
- Seaborn
- Data acquisition
- Web API
- Web scrapping
- Beautifulsoup
- Tweepy
2. Probability & Applied Statistics
- Probability
- Bayes Theorem
- Distributions
- Descriptive Statistics, outlier treatment
- Confidence level
- Central limit theorem
- Hypothesis test, AB testing
- ANOVA
- Correlation
- EDA, Feature Engineering, Missing value treatment
- Experiment Design
- Regex, NLTK, OpenCV
3. Product Analytics
- Framework to address product sense questions
- Diagnostics
- Metrics, KPI
- Product Design & Development
- Guesstimates
- Product Cases from Netflix, Stripe, Instagram
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
Duration: 8 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.
Topics that will be covered:
1. Advanced Python
- Python Refresher
- Basics of Time and Space Complexity
- OOPS
- Functional Programming
- Exception Handling and Modules
2. Math for Machine learning
- Classification
- Hyperplane
- Halfspaces
- Calculus
- Optimization
- Gradient descent
- Principal Component Analysis
3. Introduction to Neural Networks & Machine learning
- Introduction to Classical Machine Learning
- Linear Regression
- Polynomial, Bias-Variance, Regularisation
- Cross Validation
- Logistic Regression-2
- Perceptron and Softmax Classification
- Introduction to Clustering, k-Means
- K-means ++, Hierarchical
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 - TRANSITION TO TOP PRODUCT COMPANIES AT DATA ANALYTICS ROLE
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:
- Building a strong profile
- Applying the right way
- Acing the interview
We focus on all the above 3 objects in this phase.
Topics that will be covered:
Placement Support Includes:
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
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.
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
Module 5 - SPECIALIZATION IN MACHINE LEARNING AND/OR DEEP LEARNING
Duration: 8 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 ( 8 WEEKS )
1. Supervised Learning
- MLE, MAP, Confidence Interval
- Classification Metrics
- Imbalanced Data
- Decision Trees
- Bagging
- Naive Bayes
- SVM
2. Unsupervised Learning
- Intro 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
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 - MACHINE LEARNING OPS + DATA STRUCTURES & ALGORITHMS
Duration: 4 Weeks(Optional)
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
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 7 - TRANSITION TO DATA SCIENCE ROLE
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:
- Building a strong profile
- Applying the right way
- Acing the interview
We focus on all the above 3 objects in this phase.
Topics that will be covered:
Placement Support Includes:
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
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.
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 VeteransInstructors & 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.
Our Alumni Placed At :
Bosscoder is a platform to:
- 1. Upskill in Data Science concepts with Hands-on projects, using Datasets from real companies.
- 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!
Helping ambitious learners upskill themselves & shift to top product based companies.
Apply now
Next Batch starts on September