Full Stack Data Analytics Career Path For Banking and Finance
Become a fully fledged data analyst with our Full Stack Data Analytics Bootcamp that takes you from beginner to job-ready in just 4 months through industry-oriented learning.
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About This Course
What You'll Learn
Core Data Analytics Algorithms and tools
- Predictive modeling for categorical outcomes.
- Ensemble Machine Learning Techniques.
- Statistical modeling.
- Advanced Machine Learning.
- Time Series Forecasting.
- Data Visualization and Storytelling
Communication, Presentation & Business Skills
- Clarity in presenting findings, insights, and recommendations through reports or presentations.
- Ability to convey complex technical concepts to non-technical stakeholders.
- Proficiency in data visualization techniques to communicate information effectively.
- Precision in documenting processes, methodologies, and findings.
- Vigilance in spotting errors or discrepancies within datasets.
Problem Solving and Design Thinking
- Ability to break down complex problems into manageable components.
- Ability to approach problems objectively and evaluate evidence logically.
- Capacity to assess data quality, identify biases, and challenge assumptions.
- Skill in formulating hypotheses and designing experiments to test them.
Core Data Analyst Skills
- Proficiency in interpreting data and drawing meaningful insights.
- Capacity to identify trends, patterns, and outliers within datasets.
- Understanding of statistical methods and probability theory.
- Capability to perform calculations, statistical analysis, and modeling.
- Thoroughness in examining data for accuracy, completeness, and consistency.
Curriculum Designed For Career Success
Module 1: Python and SQL for Data Science
6 Lectures
Discover the power of Python for analyzing data and SQL for managing databases. Get ready to start your own data analysis journey with Python's versatile tools and SQL's database querying capabilities.
- 1.1 Python Basics:
- Understanding Python syntax and data types.
- 1.2 Object-Oriented Programming (OOPs):
- Implementing classes and objects.
- 1.3 Control Structures and Functions:
- Using conditional statements and functions.
- 1.4 Data Structures:
- Manipulating lists, tuples, dictionaries, and sets.
- 1.5 Python Libraries for Data Science:
- Utilizing Numpy, Pandas, Matplotlib, and Seaborn for data analysis.
- 1.6 SQL:
- Database design, creation, and querying using MySQL Workbench.
Module 2: Exploratory Data Analysis and Shell Scripting
3 Lectures
Uncover hidden insights in data and automate tasks with ease. Learn how to explore and clean data effectively while automating tasks using shell scripting. Gain practical skills to kickstart your data analysis projects.
- 2.1 Exploratory Data Analysis (EDA):
- Data sourcing, cleaning, univariate, bivariate, and multivariate analysis.
- 2.2 Unix and Shell Scripting:
- Basic shell scripting for automating tasks.
- 2.3 Basic Excel:
- Data manipulation and analysis using Microsoft Excel.
Module 3: Statistics and Hypothesis Testing
6 Lectures
Understand the stories behind the numbers and make informed decisions. Learn essential statistical concepts and hypothesis testing techniques to draw meaningful conclusions from data. Get ready to interpret data with confidence.
- 3.1 Descriptive and Inferential Statistics:
- Understanding data distributions and making inferences.
- 3.2 Probability:
- Probability theory and its applications.
- 3.3 Distributions:
- Discrete and continuous probability distributions.
- 3.4 Central Limit Theorem:
- Understanding the behavior of sample means.
- 3.5 Linear Algebra and Calculus:
- Basic concepts for machine learning.
- 3.6 Hypothesis Testing:
- A/B testing, Chi-squared test, ANOVA.
Module 4: ML for Data Analysis & Data Storytelling
8 Lectures
Harness the power of machine learning to uncover patterns and tell compelling stories with data. Dive into predictive modeling, time series analysis, and data visualization techniques. Equip yourself to create impactful data-driven narratives.
- 4.1 Machine Learning:
- Supervised and unsupervised learning.
- 4.2 Linear Regression:
- Predictive modeling for continuous variables.
- 4.3 Logistic Regression:
- Predicting categorical outcomes.
- 4.4 Clustering:
- Unsupervised learning for grouping similar data points.
- 4.5 Advanced Machine Learning:
- Tree models, decision trees, ensembles, random forests.
- 4.6 Time Series Forecasting:
- Techniques for analyzing and forecasting time series data.
- 4.7 Data Visualization and Storytelling:
- Communicating insights using Tableau or PowerBI, Excel, and structured problem-solving frameworks.
- 4.8 Structured Problem Solving and Frameworks:
- Business problem-solving methodologies like 5Ws, 5 Whys, Business Model Canvas, Issue Tree Frameworks, and Operations Research using Pyomo.
Module 5: Business Fundamentals (Optional)
2 Lectures
Enhance your professional toolkit with essential business communication and soft skills. Learn how to communicate effectively and collaborate with others in a business setting. Get ready to excel in your professional journey.
- 5.1 Business Communication:
- Effective communication in a business context.
- 5.2 Soft Skills:
- Interpersonal skills crucial for professional success.
Case Studies
Industry Case Studies You Will Work On
Risk Assessment with Deep Learning
Predict the likelihood of credit default for loan applicants, helping risk analysts and credit officers improve loan approval processes and reduce default rates.
Skills learned:
Data Preprocessing
Feature Engineering
Model Evaluation
Customer Behavior Analysis
Analyze customer behavior patterns to predict future actions, such as account closure or product churn, enabling targeted strategies for customer retention.
Skills learned:
Sequential Data Processing
Time Series Analysis
Predictive Modeling
Fraud Detection Using Deep Learning
Detect fraudulent transactions in real time by analyzing transaction data patterns, improving fraud detection capabilities and reducing financial losses.
Skills learned:
Anomaly Detection Techniques
Feature Extraction
Model Evaluation
Customer Sentiment Analysis
Analyze customer sentiments from feedback data to gauge satisfaction levels, helping teams identify areas for improvement in banking services.
Skills learned:
Natural Language Processing (NLP)
Sentiment Analysis Techniques
Chatbot Development for Customer Service
Develop AI-powered chatbots to handle customer inquiries and provide instant assistance, improving customer experience and service efficiency.
Skills learned:
Natural Language Processing (NLP)
Conversational AI
Model Deployment
Investment Portfolio Optimization
Optimize investment portfolios by predicting asset performance and rebalancing strategies, helping wealth managers enhance returns and manage risks effectively.
Skills learned:
Time Series Analysis
Predictive Modeling
Portfolio Optimization Techniques
Loan Approval Automation
Develop an automated system to assess loan applications, reducing manual intervention and accelerating loan processing for improved efficiency.pre
Skills learned:
Predictive Modeling
Risk Assessment Techniques
Model Deployment
Predictive Pricing Models
Develop predictive models to forecast pricing trends and optimize strategies, enabling pricing teams to align product pricing with market dynamics.
Skills learned:
Time Series Analysis
Predictive Modeling
Pricing Analytics
Predictive Lending Models
Develop personalized lending models to offer tailored loan products, helping credit departments improve customer satisfaction and portfolio performance.
Skills learned:
Predictive Modeling
Customer Segmentation
Personalized Recommendation Systems
Network Intrusion Detection
Detect and prevent cyberattacks by analyzing network traffic patterns, strengthening cybersecurity measures and protecting sensitive banking data.
Skills learned:
Intrusion Detection Techniques
Anomaly Detection
Cybersecurity Fundamentals
Advanced Fraud Detection Techniques in Banking
Learn the skills and knowledge to detect fraudulent activities in credit card transactions, ensuring financial security and reducing losses from fraud.
Skills learned:
Data Preprocessing
Feature Engineering
Model Evaluation
Anomaly Detection Techniques
Customer Segmentation Strategies
Learn how to segment customers based on their behavior and demographics to optimize marketing campaigns for targeted engagement and retention.
Skills learned:
Data Visualization
Clustering Algorithms
Customer Profiling techniques
Operational Efficiency Optimization
Develop tools and techniques to forecast call volumes in customer service centers, improving resource allocation and enhancing service efficiency.
Skills learned:
Time Series Analysis
Model Evaluation
Operational Optimization Techniques
Sales Prediction and Optimization
Learn how to predict sales performance and optimize strategies for products and services to drive revenue growth and customer acquisition.
Skills learned:
Predictive Modeling
Sales forecasting
Model Interpretation Techniques
Real-Time Fraud Detection
Equip yourself with the skills to detect fraudulent activities in real-time transactions, safeguarding organizations from financial losses.
Skills learned:
Data Preprocessing
Pattern Recognition
Anomaly Detection Techniques
Predictive Modeling for Risk Assessment
Predict default probabilities to assess risk and make informed decisions, helping organizations manage portfolios more effectively.
Skills learned:
Feature Engineering
Risk Assessment
Model Evaluation Techniques
Predictive Analytics for Customer Lifetime Value Estimation
Learn how to estimate the lifetime value of customers, enabling personalized marketing strategies and enhancing customer experiences.
Skills learned:
Customer Segmentation
Predictive Modeling
Customer Lifetime value calculation techniques
Personalized Cross-Selling Recommendations
Gain the skills to build recommendation systems for cross-selling products and services based on customer behavior and preferences.
Skills learned:
Collaborative Filtering
Recommendation Algorithms
Customer Profiling techniques
Machine Learning for Risk Assessment
Learn the tools to assess risks in decision-making processes, enabling better strategies and management for large-scale operations.
Skills learned:
Feature Selection
Risk Modeling
Credit Scoring Techniques
Automated CI/CD Pipeline for ML Models
Develop an automated CI/CD pipeline to streamline the deployment of machine learning models, ensuring quick and reliable integration into production environments.
Skills learned:
Pipeline Design
Automated Testing
Continuous Deployment
Real-Time Model Monitoring and Drift Detection
Set up real-time monitoring systems to track ML model performance and detect model drift, ensuring accuracy and reliability in changing environments.
Skills learned:
Performance Monitoring
Drift Detection
Metric Logging
Scalable Model Deployment with Docker and Kubernetes
Learn to containerize ML models using Docker and deploy them at scale with Kubernetes for reliable, efficient, and reproducible production environments.
Skills learned:
Containerization
Orchestration
Scalable Deployment
Data Versioning and Governance Framework
Design a robust data versioning and governance framework to ensure reproducibility, data integrity, and compliance with industry regulations.
Skills learned:
Data Version Control
Compliance
Governance Frameworks
Hyperparameter Tuning for Model Optimization
Implement hyperparameter tuning techniques to improve the performance of ML models, ensuring they meet production requirements effectively.
Skills learned:
Hyperparameter Tuning
Experiment Tracking
Model Optimization
End-to-End Workflow with TensorFlow Extended (TFX)
Build an end-to-end ML pipeline using TensorFlow Extended (TFX), including data ingestion, preprocessing, model training, and deployment.
Skills learned:
Pipeline Construction
Data Preprocessing
Model Deployment
Implementing Monitoring for Ethical AI Compliance
Design monitoring systems to ensure ML models align with ethical AI practices, addressing issues such as bias detection and fairness.
Skills learned:
Bias Detection
Fairness Metrics
Ethical AI Monitoring
Multi-Model Deployment and Load Balancing
Deploy multiple machine learning models in production and implement load balancing strategies to ensure efficient resource utilization and response times.
Skills learned:
Multi-Model Serving
Load Balancing
Resource Optimization
Image Enhancement and Filtering
Learn to enhance image quality using basic image processing techniques like blurring, sharpening, and edge detection. This foundational skill is crucial for preparing images for further analysis.
Skills learned:
Image filtering
edge detection
blurring
sharpening
Basic Object Detection in Images
Understand how to detect objects within images using bounding boxes and simple detection algorithms. Lay the groundwork for developing systems that can identify objects in various scenarios.
Skills learned:
Object detection
bounding box creation
using detection algorithms
Image Classification of Everyday Objects
Train a simple CNN to classify images into categories like animals, vehicles, or everyday items. This project introduces you to deep learning concepts and how they’re applied in image classification.
Skills learned:
Image classification
CNN basics
training deep learning models
Face Detection in Photos
Learn to detect faces in photos using algorithms like Haar cascades. This hands-on project provides a foundation in object detection and recognition systems.
Skills learned:
Face detection
Feature recognition
Algorithm implementation
Panorama Stitching
Combine multiple images to create seamless panoramic views using keypoint detection, feature matching, and image alignment techniques.
Skills learned:
Keypoint detection
Feature matching
Image stitching
Tracking Moving Objects in Videos
Track objects like moving balls or people in a video sequence using basic tracking algorithms. This project introduces the essentials of object tracking and algorithm implementation.
Skills learned:
Object tracking
Video analysis
Tracking algorithm implementation
Color-Based Image Segmentation
Segment images into meaningful regions by identifying specific colors and grouping similar pixels. Learn how segmentation techniques are used in organizing image content.
Skills learned:
Image segmentation
Color detection
Pixel classification
Edge Detection for Shape Identification
Detect edges in images to identify shapes and structures. This project focuses on preprocessing techniques that lay the foundation for more advanced computer vision tasks.
Skills learned:
edge detection
shape identification
Preprocessing techniques
Make A Life-Changing Career Choice
IN-DEMAND CAREER
45%
Growth in demand for Data Scientists in the next 5 years
MASSIVE JOB OPENINGS
1M +
Job openings and counting for Data Scientists worldwide.
BIGGEST GROWING INDUSTRY
$349.6 Billion
Amount industry is set to grow by 2030
HIGH ENTRY- LEVEL SALARY
₹8-14 LPA+
Current average CTC for entry-level Data Scientists in India.
Related Courses and Paths
Don't Just Learn. Specialize.
India's only course with industry specialization in the domain of your choice.
50+
Industry case studies
10+
Problem solving frameworks
Experience 360° deep specialized learning
50+
Assignments
10+
Industry Projects
100+
Hours of Learning
Learn with Ai
Our program incorporates modern Gen AI based workflows for data science so that you are equipped with the tools of the future.
Made for working professionals
Enjoy flexible learning options. Go at your own pace or learn through live classes with industry experts.
Placement support from dedicated counselors
Mock interviews with senior industry leaders
Craft the perfect resume
Access our network of partner companies
Land Your Dream Job With
Full Placement Support
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Craft a Winning Resume
Get expert help building a resume that showcases your data skills.
Nail Your Interview
Practise mock interviews with our experienced mentors to ace the recruitment process.
Company Screening & Selection
Benefit from our extensive industry network and connections to unlock exciting career opportunities.
The team was thrilled with the quality of instruction provided. We have requests from teams from other departments to undertake the training as well.
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Avinash Purohit
DGM, Canara Bank
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Is This Course Right For You?
Are you looking for a career change?
Do you want to switch from your current job to a more rewarding and in-demand career?
Do you want a promotion?
Are you a working professional looking to upgrade your career with the most sought after skill in today’s job market?
Are you a beginner to data science?
Are you a complete beginner to data science with no coding background who’s looking for a comprehensive program that teaches you everything you need to know from scratch?
If you answered ‘Yes’ to any of the above, SkillCamper’s Full Stack Career Path is the perfect fit for you!
What makes us different
Youtube Tutorials& Courses
Live classes
No learner support
No access to any mentor
No live classes
No accountability
No time commitment
SkillCamper
16 weeks course
1:1 Mentorship
Access to industry experts
Live classes with experts
Dedicated academic counselors to ensure you complete course requirements
15-20 hours of time commitment per week - designed for working professionals
Other Bootcamps & Degree Programs
20-60 weeks course
1:1 support may or may not be available
Access to industry may or may not be available
Live classes only
Accountability through assignments and grading
Full-time commitment - not made for working professionals
Online Certification Program
3-4 weeks course
No learner support
No access to industry experts
No live classes
Limited accountability
8-10 hours per week of time commitment- suited to working professionals
“The mentors at SkillCamper teach very well, making all the concepts easy to understand. ”
Their teaching style is clear and effective, and I am grateful for their guidance. I hope they continue this excellent approach in the future.
Ravi Prakash
Automation Test Analyst
“SkillCamper's Data Analytics Bootcamp is fantastic. ”
I had tried learning some data analytics tools through free platforms, but it wasn't enough to get a good opportunity. SkillCamper goes beyond just teaching tools; they focus on domain expertise, which is essential today. The course material is very practical, and I feel like I'm gaining valuable skills. Highly recommended!
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Sanjay Shah
Graduate in BSC-IT
“I'm doing the Data Analytics Bootcamp at SkillCamper, and it's great. ”
Even though I don't have a tech background, the mentors explain things in a simple way that I can understand. The projects and the friendly community make learning fun and helpful. I highly recommend SkillCamper for anyone new to data analytics!
Ashish Lodhe
Graduate in BSC-IT
“The course is going well and the mentors are very supportive. ”
As a student from a non-tech background, I find their teaching style easy to follow. They explain everything in simple terms and help with any questions. I highly recommend SkillCamper for anyone starting from scratch!
Suman M-
Graduate in BSC-IT
Testimonials
Alumni Success Stories
From career switchers to college grads, we have helped a diverse range of learners kickstart & progress rapidly in their data science careers.
POPULAR
Live Interaction
Self paced
Fee Structure
₹ 75,000
₹ 50,000
Curriculum & Course Materials
Live coding environment
AI-based learning platform
100+ hours of instruction
20+ assignments
10+ industry projects
Choose your industry specialization
Capstone projects
Live Classes
Flexible study options
Cancel anytime in first 7 days, full refund
Mentors
15+ hours of sessions with industry veterans & experts
Personalized mentorship by course instructors
Unlimited 1:1 doubt solving sessions
Career Support
Personalized placement assistance
1:1 mock interviews with industry experts
Soft-skills training module
Essential digital tools for digital workplace module
Interview preparation module
Masterclass on resume building & LinkedIn
Access to curated companies & jobs
POPULAR
Live Interaction
Self paced
Fee Structure
$599
$299
Curriculum & Course Materials
Live coding environment
AI-based learning platform
100+ hours of instruction
20+ assignments
10+ banking & finance case studies
Banking & finance domain focused curriculum
Capstone projects
Live Classes
Flexible study options
Cancel anytime in first 7 days, full refund
Mentors
15+ hours of sessions with industry veterans & experts
Personalized mentorship by course instructors
Unlimited 1:1 doubt solving sessions
Career Support
Personalized placement assistance
1:1 mock interviews with industry experts
Soft-skills training module
Essential digital tools for digital workplace module
Interview preparation module
Masterclass on resume building & LinkedIn
Access to curated companies & jobs
Frequently Asked Questions
Who is this course for?
This course is ideal for beginners, career switchers, and banking/finance professionals looking to gain data analytics skills.
Do I need any prior experience to join?
No prior experience is required. We start with the basics of data analytics, Python, and SQL.
What tools will I learn in this course?
You’ll gain hands-on experience with tools like Python, Power BI, SQL, and industry-relevant data analysis techniques.
How long is the course?
The course spans 4 months, with flexible learning options and live classes.
What real-world projects will I work on?
You will work on case studies related to fraud detection, customer segmentation, and predictive analytics in the banking industry.
Is there placement support after completing the course?
Yes, we offer placement support, including mock interviews, resume building, and access to our network of partner companies.
What if I miss a live class?
All live classes are recorded and made available for you to watch at your convenience.
Can I pause the course if needed?
Yes, we offer a 30-day pause option in case you need to take a break.
Is there a refund policy?
We have a 7-day, no-questions-asked money-back policy if you decide the course isn’t right for you.
Will I receive a certification after completing the course?
Yes, you will receive a certification upon successful completion of the course and its projects.
What type of job support do you provide after completing the course?
We offer comprehensive placement assistance, including resume building, mock interviews, and leveraging our network of industry partners.
How do you prepare students for the job market?
We equip students with industry-relevant skills, help craft winning resumes, and provide mock interview practice with experienced mentors.
Do you guarantee a job after completing the course?
While we do not guarantee a job, we provide extensive support to help you become highly competitive in the job market.
Can you help me find a job in any specific industry?
Our job assistance is generalized; we prepare you for a variety of roles in the data science field rather than focusing on specific industries.
What is the cost of the Data Science bootcamp?
The cost varies depending on the program. Our full bootcamp is priced between ₹50,000 and ₹75,000, depending on whether you choose self-paced or live instruction.
Are scholarships available for the courses?
Yes, we offer scholarships that can cover up to 70% of the tuition fees, making our courses more accessible to a wider range of students.
What is included in the course fee?
The fee includes access to all course materials, live coding sessions, AI-based learning platform, case studies, capstone projects, and mentorship from industry experts.
What payment options are available for the course fees?
We offer flexible payment options, including easy EMIs, and you can cancel anytime in the first 7 days for a full refund.
Is financial aid or other support available aside from scholarships?
While our primary financial support is through scholarships, our enrollment advisors can also assist you with payment plans and financing options to help manage the cost of your education.
Ready to become a Data Scientist that industry loves to hire? Apply Now.
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