Program Overview
Advanced Executive Certification in Data Science (DS)
Offered by: Centre for Training and Employment, CTE

Collaboration with: Council for Citizen Rights, CCR (NGO) - National Mission Technical Education for Employment Wing
Duration: 5 months 
Mode: Online and Offline

Regular Classes Start from 10th March (Monday).
Enrollments open till 10th March, Monday. Choose your preferred Weekday or Weekend Batches with timings:
1) Morning: 9:00 AM / 11:00 AM
2) Evening: 6:00 PM / 8:00 PM

For Assistance:
Call/WhatsApp: 9281434941, 9281434940, 9281434939, 9949073398
WhatsApp Only: 8072211686, 9346000855
Visit our centers for in-person guidance.

Key Features:

• 260 Hrs of SME led Training & 90 Hrs of Projects & Exercises
• LIVE in-person classroom and LIVE Online Video Classes
• Each Session Live Recordings, Study Materials, Program Files, Assignments, Projects, Quizes available in Learning Management System (LMS) Portal after the class
• Lifetime Access to Course
• 1:1 mentorship & 24/7 Technical Support till course completion & getting job
• 50+ industry projects
• Certification from the Centre for Training and Employment (MSME, ISO, AICTE)
• Guranteed Job Assistance Till Placement
• Campus immersion at India's reputed Universities, Institutions, MNCs, Industries
• Up to ₹50 Lakh startup incubation support

Our Credentials:

•  Instructors: 56+ Industry Experts  
•  Hiring Partners: 125+  
•  Corporates & Colleges Upskilled: 175+  
•  States in India with Learners: 18+  

Why Choose Data Science?

• Top Career Path
  • Data Science is one of the most in-demand job roles globally, driving decision-making in every industry.
• High Demand
  • Over 1.8 million job opportunities globally by 2025 for Data Science roles.
  • Essential for businesses to extract insights from big data.
• Attractive Salaries
  • Data Scientists earn 50–60% higher than average IT salaries.
  • A significant talent gap makes this a lucrative career.

Learning Path and Roadmap

Roadmap, Skills & Tools, Learning Path of the Course - available at LinkedIn:
https://lnkd.in/g2KAhusq

1. Preparatory Sessions: Get introduced to foundational concepts and set the stage for advanced learning.  
2. Python: Fundamentals and Programming Concepts: Master the essentials of Python programming with hands-on practice.  
3. Python Libraries for Data Science: Explore powerful libraries like NumPy, pandas, and matplotlib for data analysis.  
4. Data Wrangling with SQL: Learn to clean, transform, and manage data using SQL queries.  
5. Linear Algebra and Advanced Statistics: Dive deep into mathematical concepts essential for data science and ML.  
6. Machine Learning (ML): Build predictive models and uncover patterns in data using ML algorithms.  
7. Deep Learning: Explore neural networks and advanced AI techniques for complex problem-solving.  
8. Deploying Machine Learning Models With Cloud: Implement and scale ML models using cloud platforms.  
9. Business Intelligence & Analytics: Power BI: Transform data into actionable insights with Power BI.  
10. GIT: Collaborate efficiently with version control using GIT.

Skills

• Python Programming 
• SQL
• Story Telling
• Inferential Statistics 
• Machine Learning 
• Mathematical Modelling 
• Descriptive Statistics 
• Data Analysis 
• Generative Al  
• Supervised Learning 
• Unsupervised Learning 
• Data Visualization 
• DataAnalysis
• Data Science  
• Hypothesis Testing 
• Statistical Analysis 
• Data Wrangling

Tools

• matplotlib 
• Jupyter 
• SciPy 
• NumPy 
• Pandas 
• SQL
• Excel 
• Power BI 
• git 
• Spark SQL
• TensorFlow
• PySpark

Faculty and Advisors

•  Renowned professors
•  Industry experts

Career Services

•  Job Search Strategies  
•  Resume Building  
•  LinkedIn Profile Optimization  
•  Mock Interview Sessions with Industry Experts  
•  Placement Readiness Test  
•  Career Opportunities with 400+ Hiring Partners  

Module 1: Preparatory Sessions - Python  

•    Introduction to Python and IDEs  
•    Python Basics  
•    Object-Oriented Programming  
•    Hands-on Sessions and Assignments  

Module 2: Data Analysis with Excel  

•  Introduction to Excel for Data Science  
•  Data Cleaning and Manipulation in Excel  
•  Data Visualization with Charts and Graphs  
•  Advanced Excel Functions for Analysis  

Module 3: Python with Data Science  

•  Data Handling with NumPy  
•  Data Manipulation Using Pandas  
•  Data Preprocessing  
•  Data Visualization Using Matplotlib

Module 4: Data Wrangling with SQL  

•  SQL Basics  
•  Advanced SQL  
•  User-Defined Functions  
•  SQL Optimization and Performance  

Module 5: Linear Algebra and Advanced Statistics  

•  Descriptive Statistics  
•  Probability  
•  Inferential Statistics  
•  Linear Algebra  

Module 6: Machine Learning  

•  Introduction to Machine Learning  
•  Regression Techniques  
•  Classification Techniques  
•  Clustering Methods  

Module 7: Supervised Learning  

•  Linear Regression  
•  Logistic Regression  
•  Decision Trees  
•  Random Forests and More

Module 8: Unsupervised Learning  

•  K-Means Clustering  
•  Dimensionality Reduction:  
•  Principal Component Analysis (PCA)  
•  Linear Discriminant Analysis (LDA)  

Module 9: Deep Learning Using TensorFlow  

•  Basics of Artificial Intelligence  
•  Neural Networks  
•  Advanced Deep Learning  

Module 10: Data Science Capstone Project  

•  Data Extraction, Loading, and Transformation  
•  Data Manipulation and Preprocessing  
•  Feature Engineering and Scaling  
•  Model Selection and Implementation:  
•  Supervised and Unsupervised Algorithms  
•  Regression and Classification Tasks  
•  Model Evaluation and Monitoring  

Module 11: Business Case Studies  

•  Recommendation Engine  
•  Rating Predictions  
•  Census Analysis  
•  Housing Price Prediction  
•  Object Detection  
•  Stock Market Analysis  
•  Banking Problem Solving  
•  AI Chatbot Development  

Module 12: Power BI (Elective)

•  Basics of Power BI  
•  Data Analysis Expressions (DAX)  
•  Data Visualization with Analytics  

Module 13: Deploying Machine Learning Models with Cloud (Elective)  

•  Introduction to MLOps  
•  Cloud Deployment of Machine Learning Models  

Module 14: GIT (Elective)  

•  Version Control Systems  
•  GIT for Collaboration and Workflow Management  

Beginner Projects
1. Face Detection  

•     Industry Sector: Security, Surveillance, Healthcare  
•     Use Python 3.5 (64-bit) with OpenCV for face detection. Ensure the system detects multiple faces in a single image. Utilize libraries such as `cv2` and `glob` for image processing and detection, ideal for security systems and healthcare applications like patient tracking.

2. Restaurant Revenue Prediction  

•     Industry Sector: E-Commerce, Retail, Food and Beverage  
•     Predict annual restaurant sales using features like opening date, city type, and restaurant type. Use packages like `caret`, `Boruta`, and `dplyr` for dataset analysis and sales prediction. This project applies to predicting business trends and sales forecasting in the restaurant industry.

Intermediate Projects
3. Work with PySpark and RDD  

•     Industry Sector: Big Data, Cloud Computing, Finance  
•     Utilize PySpark, a Python API for Spark, and RDD via the Py4J package. Configure and run a Spark application using `SparkConf`. This project is ideal for industries dealing with large-scale data processing, like finance and big data analytics.

4. Build the Book Recommender Application  

•     Industry Sector: E-Commerce, Media, Entertainment  
•     Create a book recommender engine using a user-based collaborative filtering model. Use packages like `recommenderlab`, `dplyr`, `tidyr`, `stringr`, and `corrplot`. The project is essential for platforms like Amazon or Goodreads, providing personalized recommendations.

5. Census Project  

•     Industry Sector: Government, Public Policy, Demographics  
•     Work with census income data from the UCI Machine Learning repository. Handle missing values and predict the annual income of individuals using data handling techniques. This project is applicable in government data analysis and demographic studies for policy making.

Advanced Projects
6. Housing Price Prediction  

•     Industry Sector: Real Estate, Finance  
•     Predict sale prices of houses using 79 explanatory variables in the dataset. Gain practical experience with dataset preprocessing and predictive modeling. This project is relevant to real estate agents, property investment analysts, and the housing market.

7. HR Analytics  

•     Industry Sector: Human Resources, Talent Management, Business Intelligence  
•     Analyze HR analytics datasets to address HR-related problem statements. Understand the dataset features and evaluate the model with metric identification processes. Useful for talent management, employee retention, and workforce planning in large organizations.

8. Joke Rating Prediction  

•     Industry Sector: Entertainment, Social Media, Customer Experience  
•     Build a model to predict user ratings for jokes using the Jester online joke recommender dataset. Apply techniques for handling missing values and model evaluation. This project applies to the entertainment and social media sectors where user engagement and content recommendation are essential.

9. Build Recommendation Engine  

•    Industry Sector: E-Commerce, Media, Entertainment  
•    Develop a movie recommender engine using the SVD algorithm. Handle missing values and use libraries like `NumPy`, `Pandas`, and `matplotlib`. This project is ideal for streaming platforms like Netflix or Amazon Prime, where user preferences are analyzed to recommend personalized content.

Industry Applications
 Retail  

•     Projects like Restaurant Revenue Prediction, Census Project, and HR Analytics are applicable to the retail sector, helping businesses analyze sales, predict trends, and manage workforce data effectively.

 Social Media  

•     Projects such as Joke Rating Prediction and Face Detection have applications in social media platforms, helping companies personalize content and enhance user engagement.

 Supply Chain and E-commerce  

•     Projects like Book Recommender Application and Build Recommendation Engine are essential for e-commerce platforms that require personalized recommendations and product predictions.

 Finance and Banking  

•     Projects such as Work with PySpark and RDD and Housing Price Prediction are crucial for big data processing and financial modeling, helping in decision-making and investment strategies in the finance sector.

 Healthcare  

•     Face Detection and Joke Rating Prediction can be used in healthcare for patient monitoring and entertainment in patient care services.

 Government  

•     The Census Project plays a significant role in government data analysis for public policy decisions and demographic studies.

Job Opportunities / Roles

Learning data science opens up a wide range of job opportunities across various industries. Here are some common job roles and industries where data scientists are in demand:

1. Data Scientist (₹8–18 LPA): Analyzing complex datasets, building predictive models, and deriving insights to help organizations make data-driven decisions.  
2. Machine Learning Engineer (₹9–20 LPA): Designing, implementing, and deploying machine learning models for solving specific business problems.  
3. Data Analyst (₹5–10 LPA): Analyzing and interpreting data to help organizations make informed decisions. Data analysts often focus on descriptive analytics and reporting.  
4. Business Intelligence (BI) Analyst (₹6–12 LPA): Using data to provide insights into business performance, trends, and areas for improvement. BI analysts work with tools like Tableau, Power BI, and others.  
5. Data Engineer (₹7–16 LPA): Developing, constructing, testing, and maintaining architectures (e.g., databases, large-scale processing systems) for data generation.  
6. Quantitative Analyst (₹10–25 LPA): Applying mathematical and statistical methods to financial and risk management problems in industries such as finance and insurance.  
7. Operations Analyst (₹5–9 LPA): Optimizing and improving business operations using data-driven insights.  
8. Statistician (₹6–14 LPA): Applying statistical techniques to analyze and interpret data. Statisticians work in various fields, including healthcare, government, and research.  
9. AI Research Scientist (₹12–30 LPA): Conducting research to develop new algorithms and techniques for artificial intelligence and machine learning.  
10. Data Product Manager (₹10–22 LPA): Managing the development of data-driven products and ensuring they align with business goals.  
11. Healthcare Data Analyst (₹6–12 LPA): Analyzing healthcare data to improve patient outcomes, optimize healthcare processes, and support decision-making in the healthcare industry.  
12. Supply Chain Analyst (₹6–13 LPA): Applying data science techniques to optimize supply chain processes, reduce costs, and improve efficiency.  
13. Marketing Analyst (₹5–11 LPA): Analyzing marketing data to understand customer behavior, optimize campaigns, and improve overall marketing strategies.  
14. Cybersecurity Analyst (₹7–15 LPA): Using data science techniques to detect and prevent cyber threats, as well as analyzing security logs and patterns.  
15. Environmental Data Scientist (₹6–12 LPA): Applying data science to analyze environmental data, monitor climate change, and support sustainable practices.  
16. Educational Data Analyst (₹5–10 LPA): Analyzing educational data to improve student outcomes, optimize learning environments, and support educational decision-making.

Program Pedagogy

•  Flexible learning (live and self-paced sessions)  
•  Gamified exercises and group projects  
•  Real-world capstone projects

About Centre for Training and Employment (CTE):

CTE is a leading online education provider, and also classroom / offline services partnering with prestigious colleges and industries, consultants.

Mission: Democratizing education with cutting-edge training solutions. 

Placement Sources

1. Premium Job Portals:

•      Naukri, LinkedIn, Glassdoor, Monster, and Indeed for job matching and direct applications.

2. Hiring Companies Requirement List:

•      Regular updates from partnered companies about open roles and skill demands.

     Industry-specific collaborations (e.g., IT, Banking, Healthcare, E-commerce).

3. HR Connections:

•     Build a network of HR professionals for referrals and insights into recruitment trends.

    Conduct periodic meetups and webinars with HR executives.

4. Consultations and Industry Experts:

•     Collaborate with career consultants and market experts to refine placement strategies.

5. Recruitment Agencies:

•     Partnerships with top recruitment agencies for exclusive job openings.

6. Company Tie-Ups:

•      Direct collaborations with companies for hiring events and job drives.

7. Internship Providers:

•      Companies offering internships, leading to pre-placement offers (PPOs).

8. Freelance and Gig Platforms:

•       Platforms like Upwork, Toptal, and Fiverr for freelance and contract-based work opportunities.

9. Networking Events:

•       Job fairs, industry conferences, and alumni networking for connecting with employers.

10. Technology Tools:

•      Use of Applicant Tracking Systems (ATS) and AI-driven tools for job search optimization.

Flexible Fee Structure and Payment Options

• At CTE Academy, we aim to make quality education accessible and affordable for everyone. 
• Explore our flexible fee categories, scholarships, and EMI options tailored to suit your financial needs.

Fee Categories

• Training Only: ₹17,500
• Training and Placement: ₹28,500 (EMI Options available)

• Book for Offline - Classroom (Hyderabad, Vijayawada, Siddipet) / Work and Learn:
  • Reserve Seat for ₹3,000
  • Fees structure same as Online via LMS
• Pay After Placement:
  • Before Placement: ₹17,500
  • After Placement: ₹58,500

Scholarship Program

• Who Can Apply: Unemployed and underprivileged candidates
• Scholarship Amount: 10% to 40% off on the One-Time Payment (OTP) fees

Exclusive EMI Plans - CTE Academy via Unacademy (Graphy) Collaboration with several organizations:

• Make learning stress-free with our easy-to-manage EMI options. 

"Education made easy – success made inevitable!"