Program Overview
Advanced Executive Certification in Data Science & Artificial Intelligence & Machine Learning
Offered by: Centre for Training and Employment, CTE
Collaboration with: Council for Citizen Rights, CCR (NGO)
Duration: 3 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:

•  120 hours of applied learning
•  Live In in-person classroom and Video Classes
• Each Session Live Recording is available in the Learning Management System (LMS) Portal
•  Lifetime Access to Course
•  1:1 mentorship
•  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:

•  Certified & Placed Students: 75 Thousand+  
•  Instructors: 56+ Industry Experts  
•  Hiring Partners: 125+  
•  Corporates & Colleges Upskilled: 175+  
•  States in India with Learners: 18+  

Versatile Career Opportunities: Python is one of the most widely used programming languages, powering diverse domains like web development, data science, AI, machine learning, automation, and game development.

High Demand: Python ranks among the top 3 most popular programming languages globally, with demand for Python developers expected to grow by over 25% annually across industries.

Salary Potential: Python professionals earn 40–60% higher salaries than developers in other languages, as organizations increasingly rely on Python for its simplicity and versatility.

Skill Development: Start with the basics (syntax, loops, and functions) and progress to advanced topics like object-oriented programming (OOP), file handling, web frameworks (Django/Flask), data manipulation (Pandas), and machine learning libraries (NumPy, Scikit-learn) to become a well-rounded Python expert.

Learning Path and Roadmap

Roadmap, Skills & Tools, Learning Path of the Course - available at LinkedIn:
 

• Python Basics, Constructs, and Environment Setup  
• OOP Concepts, Exception Handling, and Multithreading  
• Database Connectivity, NumPy, and SciPy  
• Data Visualization (Matplotlib) and Analysis (Pandas)  
• Advanced Web Scraping and Final Projects 

Skills to Master

• Python Basics
• Object-Oriented Programming (OOP)  
• Database Connectivity  
• NumPy, SciPy, and Matplotlib  
• Pandas and Data Analysis  
• Exception Handling  
• Multithreading  
• Web Scraping  

Tools You'll Use

•  Python IDEs (e.g., Anaconda, Jupyter Notebook)  
•  MySQL  
•  Libraries: BeautifulSoup, NumPy, SciPy, Matplotlib, Pandas

Faculty and Advisors

•  Renowned professors
•  Industry experts

Career Services

•  1:1 Mock Interviews  
•  Dedicated Placement Support  
•  Career Fairs and Resume Building  
•  Access to 200+ job postings monthly  

Modules and Topics
1. Python Environment Setup and Essentials  

•     Introduction to Python language and features  
•     Advantages over other languages  
•     Installation on Windows, Mac, Linux, and Anaconda Python  
•     Python IDE deployment  
•     Basic Python commands, data types, variables, and keywords  

2. Python Language Basic Constructs  

•     Built-in data types and basic operators  
•     Logical, comparison, arithmetic, and slicing operations  
•     Control statements: `while`, `for`, `if`, `break`, `else`, `continue`  

3. OOP Concepts in Python  

•     Writing object-oriented programs  
•     Classes, objects, inheritance, polymorphism, encapsulation  
•     Lambda expressions and database connectivity  

4. Database Connections  

•     Database basics and MySQL installation  
•     Python database connections  

5. NumPy for Mathematical Computing  

•     Arrays, matrices, and broadcasting  
•     Array math, indexing, and statistical operations (e.g., correlation, covariance)  

6. SciPy for Scientific Computing  

•     Advanced mathematical operations using SciPy  
•     Clustering, linear algebra, signal processing, optimization  

7. Matplotlib for Data Visualization  

•     Plotting graphs and charts (line, scatter, bar, histogram, 3D)  
•     Matplotlib APIs and subplots 

8. Pandas for Data Analysis and Machine Learning  

•     Working with data frames  
•     Importing data (JSON, CSV, Excel, SQL)  
•     Data operations: filtering, sorting, joining, combining  

9. Exception Handling  

•     Exception scenarios, raising exceptions  
•     Arithmetic and value errors  

10. Multithreading & Race Condition  

•      Thread operations, synchronization, and race conditions  
•      Creating and managing multithreads  

11. Packages and Functions  

•      Python modules and package management  
•      Decorators, namespace, and scoped functions  

12. Web Scraping  

•      Libraries like BeautifulSoup, Scrapy, lxml  
•      Parsing HTML, tree searching, and scraping automation  

Projects & Applications of Python
Data Analysis and Visualization  
1. Analyzing Naming Patterns  

•     Work with data from the US Social Security Administration (SSA)  
•     Analyze baby name frequency trends from 1880 to 2016  
•     Visualize trends using Matplotlib and Pandas  

2. Customer Churn Analysis  

•     Analyze employment reliability in the telecom industry  
•     Perform real-time data analysis using NumPy and Pandas  
•     Create data visualizations to interpret multi-label datasets  

3. Retail Sales Prediction  

•     Analyze historical sales data to predict future trends  
•     Use NumPy, Pandas, and Matplotlib for data wrangling and visualization  

4. Healthcare Data Analysis  

•     Explore patient admission and discharge data  
•     Perform correlation analysis on symptoms and treatments  

Web Scraping and Automation  
5. Python Web Scraping for Data Science  

•     Work with web scraping libraries like BeautifulSoup, Scrapy, and Selenium  
•     Extract and clean data from e-commerce or social media websites  

6. Real-Time Weather Data Scraping  

•     Collect weather data from APIs or websites  
•     Automate daily updates and visualize trends over time  

7. Job Listings Scraper  

•     Develop a scraper for job boards like LinkedIn or Indeed  
•     Analyze job trends based on location, skill sets, and company demand  

Machine Learning Projects  
8. House Price Prediction  

•     Build a regression model using SciKit-Learn  
•     Use datasets with features like location, size, and amenities  

9. Sentiment Analysis on Movie Reviews  

•     Analyze and classify reviews into positive or negative sentiments  
•     Use Natural Language Processing (NLP) and Python libraries like NLTK  

10. E-commerce Product Recommendation System  

•      Implement a collaborative filtering algorithm  
•      Use purchase history to recommend products  

Advanced Python Concepts  
11. Multi-threaded Web Server  

•      Create a web server to handle multiple client requests simultaneously  
•      Use Python’s threading and socket libraries  

12. Automated Email System  

•      Develop a system to send customized emails based on user inputs  
•      Incorporate SMTP and MIME libraries  

13. Data Encryption and Decryption Tool  

•      Implement basic cryptography algorithms like Caesar cipher or AES  
•      Build a GUI for user interaction  

Industry-Specific Projects  
14. Banking Fraud Detection  

•      Analyze banking transaction data  
•      Use classification algorithms to detect fraudulent activities  

15. Social Media Trend Analysis  

•      Scrape social media platforms for trending hashtags or posts  
•      Perform time-series analysis using Pandas  

16. Inventory Management System  

•      Build a simple inventory tracker for retail businesses  
•      Use SQL for database integration  

Capstone Projects  
17. End-to-End Data Pipeline  

•      Collect, clean, and analyze a real-world dataset  
•      Build a dashboard for real-time data visualization  

18. Traffic Flow Prediction  

•      Use historical traffic data to predict congestion levels  
•      Apply time-series analysis and visualize with Matplotlib  

19. Stock Price Forecasting  

•      Predict stock prices using historical data and ML algorithms  
•      Include moving averages and Bollinger Bands in the analysis  

20. Chatbot Development  

•      Build a chatbot using Natural Language Processing (NLP)  
•      Train the bot to answer FAQs or assist users

Job Roles / Opportunities - Python:

1. Software Developer/Engineer: 

Develop software applications, systems, and solutions using Python.Opportunities in web development, desktop applications, and backend systems.

2. Data Scientist: 

Analyze and interpret complex datasets using Python libraries such as Pandas, NumPy, and scikit-learn. Build machine learning models and perform statistical analysis.

3. Machine Learning Engineer:

 Design, build, and deploy machine learning models and systems using Python. Implement algorithms, work with neural networks, and optimize models for performance.

4. Data Engineer: Create and maintain data architectures, databases, and data processing pipelines using Python. Work with tools like Apache Spark and Hadoop for big data processing

5. DevOps Engineer: Automate infrastructure provisioning, deployment, and monitoring using Python. Implement continuous integration and continuous deployment (CI/CD) pipelines.

6. Full Stack Developer: 

Build end-to-end web applications using Python for both frontend and backend development. Utilize frameworks like Django or Flask for backend development.

7. Network Engineer/Scripting Engineer:

 Use Python for network automation, scripting, and configuration management.  Streamline network processes and enhance efficiency.

8. Cybersecurity Analyst:

Employ Python for security analysis, penetration testing, and automation. Develop tools for security monitoring and incident response.

9. Game Developer:

 Create and develop games using Python and game development libraries such as Pygame.  Python is often used for scripting and gameplay logic.

10. Quantitative Analyst/Financial Analyst:

 Use Python for financial modeling, risk analysis, and algorithmic trading. Work with libraries like pandas, NumPy, and financial Python libraries.

11. GIS (Geographic Information System) Developer: Develop geospatial applications and mapping solutions using Python.  Work with libraries like GeoPandas and Folium.

12. Cloud Engineer: Implement cloud solutions, manage resources, and automate tasks using Python. Work with cloud platforms like AWS, Azure, or Google Cloud.

13. Automation Testing Engineer:  Write automated test scripts using Python to ensure the quality of software products. Use frameworks like Selenium, pytest, or Robot Framework.

14. Freelancer/Consultant: Offer your Python programming skills as a freelancer or consultant. Work on various projects across different industries based on your expertise

Innovative Features:  

•  Learn by Doing: Hands-on exercises, projects, quizzes, assignments and capstone projects.
•  Gamified Learning: Hackathons and group activities.
•  Peer Networking: Build professional connections through collaborative learning.

Program Pedagogy: 

• Instructor-led Training: Delivered by top industry experts.  
• Projects and Exercises: Gain real-world experience.  
• Hackathons: Understand real-world project-building techniques.  
• Personalized Learning: Tailored 1:1 mentoring. 

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: ₹9,500
• Training and Placement:
  • One Time Payment (OTP) - ₹14,500
• Book for Offline - Classroom (Hyderabad - Ameerpet and Vijayawada) / Work and Learn / Online EMI without HDFC or without credit card.
  • Reserve Seat for ₹3000
  • Fees structure same as Online via LMS
• Pay After Placement:
  • Before Placement: ₹9,500 (EMI Options available) 
  • After Placement: ₹34,500

Scholarship Program

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

"Education made easy – success made inevitable!"