Internship Assured - Advanced Data Science Masterclass (Python, PowerBi, Machine Learning, GenAI, Flask and SQL)

  • Course Duration Weekdays (8 Weeks) /Weekends (16 Weeks)
  • Course Mode Instructor Led Online Training
  • Date & Time 28-April-2025

About The Course

This comprehensive masterclass by AiCouncil, a proud Microsoft Solution Partner and member of the AWS Partner Network, is designed to equip participants with industry-ready expertise in Python programming, SQL database management, exploratory data analysis (EDA), machine learning, deep learning, and generative AI. The course offers hands-on learning in:

* Data manipulation with Pandas

* Data visualization using Matplotlib, Seaborn, and Power BI

* Machine learning algorithms and ensemble techniques

* Generative AI applications and prompt engineering

* Model deployment using Flask

* Data analysis with Microsoft Excel

Participants will work on real-world case studies and industry-relevant projects, gaining practical experience in solving complex data problems, extracting actionable insights, and building AI-driven solutions. The program concludes with globally recognized certification, backed by Microsoft and AWS, and includes lifetime job assistance and 3 years of technical support.

Key Features

Instructor-Led, Interactive Training

Live, expert-led sessions for hands-on learning

Lifetime Access to Recordings

Revisit recorded classes anytime, at your convenience

Assignments & Real-Time Projects

Apply skills through practical projects after every module

Lifetime Job Assistance

Ongoing support for AI and Data Science job opportunities

3 Years of Technical Support

24/7 query resolution and technical help for 3 years

Globally Recognized Certification

Certified by AiCouncil, backed by Microsoft & AWS

Highlights

Comprehensive Python programming with NumPy, Pandas, Matplotlib, Seaborn, and feature engineering techniques.

Exploratory Data Analysis (EDA) including descriptive statistics, data cleaning, handling missing values, and correlation analysis.

Advanced data visualization using Power BI, including interactive dashboards, DAX functions, and AI-powered insights.

Machine learning fundamentals covering supervised and unsupervised learning, feature scaling, and model evaluation techniques.

Deep dive into Naïve Bayes, Support Vector Machines (SVM), and ensemble learning methods like Random Forest, AdaBoost, and Gradient Boosting.

Hands-on experience with Generative AI, including transformers, large language models (LLMs), and prompt engineering strategies.

Web application development and deployment of machine learning models using Flask and RESTful APIs.

SQL and MySQL database management, advanced queries, joins, and optimization techniques for efficient data handling.

Real-world case studies, industry-focused projects, and guest lectures by AI experts to provide practical exposure.

Course Agenda

  • Basic Overview
  • Variables
  • Data Types
  • Conditional Statements
  • Loops
  • Pandas
  • NumPy
  • Matplotlib
  • Seaborn
  • Data Manipulation
  • Feature Scaling and Transformation
  • Visualization
  • Statistics
  • Data Manipulation
  • Cleaning and preprocessing data using Pandas
  • Feature Scaling and Transformation
  • Using StandardScaler and MinMaxScaler
  • Visualization
  • Creating plots using Matplotlib and Seaborn
  • Basic Statistical Analysis
  • Summary statistics and data characteristics
  • Introduction to EDA
  • Descriptive Statistics
  • Data Visualization
  • Handling Missing Data
  • Identifying Outliers
  • Correlation Analysis
  • Applying EDA Techniques
  • Using Python libraries (Pandas, Matplotlib, Seaborn) to perform EDA
  • Interpreting Results
  • Drawing insights from visualizations and statistical summaries
  • Introduction to Power BI
  • Data Preparation, Modelling and Visualization
  • Power BI Dashboard and Data Transformations
  • M Query and Hierarchies
  • DAX Essentials
  • Slicers, Filters, Drill Down Reports
  • Power BI Query, Q & A, and Data Insights
  • Power BI Settings, Administration, and Direct Connectivity
  • Embedded Power BI API and Power BI Mobile
  • Power BI Advanced and Power BI Premium
  • Creating Power BI Dashboards
  • Performing Data Transformations
  • Using DAX for Advanced Data Analysis
  • Connecting Power BI to Various Data Sources
  • Introduction
  • Supervised Learning
  • Unsupervised Learning
  • Reinforcement Learning
  • K-Fold Cross-Validation
  • Confusion Matrix
  • ROC Curve
  • Linear Regression
  • Polynomial Regression
  • Logistic Regression
  • Decision Trees
  • k-Nearest Neighbors (k-NN)
  • Implementing and Evaluating Regression Models
  • Building linear and polynomial regression models
  • Implementing and Evaluating Classification Models
  • Constructing logistic regression, decision tree, and k-NN classifiers
  • Introduction to Probabilistic Classifiers
  • Understanding Naïve Bayes
  • Math behind Bayes Theorem
  • Introduction to SVM
  • Concepts and Advantages
  • Linear and Nonlinear SVM Classifiers
  • Kernel Functions
  • Classification and Regression
  • Implementing Naïve Bayes Classifiers
  • Using scikit-learn to build and evaluate probabilistic classifiers
  • Implementing SVM Classifiers
  • Applying SVM for classification tasks using different kernel functions
  • Introduction to Ensemble Methods
  • Concepts and Benefits
  • Bagging
  • Boosting
  • Stacking
  • Implementing Ensemble Algorithms
  • Building and evaluating ensemble models (Random Forest, AdaBoost, Gradient Boosting)
  • Introduction to Unsupervised Learning
  • Concepts and Applications
  • K-means Clustering
  • Hierarchical Clustering
  • Dimensionality Reduction
  • PCA
  • Implementing Clustering and Dimensionality Reduction
  • Using K-means, hierarchical clustering, and PCA for data exploration
  • Generative AI
  • Introduction, Types of Generative AI
  • Image, Text, and Audio Generation
  • Generative Adversarial Networks (GAN)
  • Long Short-Term Memory (LSTM)
  • Transformers, Hugging Face Transformers
  • BERT, GPT-3, T5
  • Large Language Models (LLM)
  • 10+ AI Tools Covered
  • Prompt Engineering
  • Introduction
  • Prompt Design
  • Zero-shot, One-shot, Few-shot prompts
  • Chain of Thought (CoT) Prompting
  • Role-Specific Prompting
  • Tree of Thoughts (ToT) Prompting
  • Application-Specific Prompts
  • Prompt Optimization, APIs for Custom Integration
  • Response Evaluation, Iterative Testing
  • Fine-tuning and Experimenting with LLMs
  • Using OpenAI’s GPT models and Hugging Face transformers
  • Prompt Optimization
  • Writing and testing various types of prompts for improved AI responses
  • Introduction to Flask for Web App Development
  • Building RESTful APIs with Flask
  • Deployment of Machine Learning Models as REST APIs
  • Developing and Deploying ML Models
  • Implementing machine learning models using Flask for REST API consumption
  • MS Excel
  • Statistical Functions, Logical Functions
  • Mathematical Functions
  • Lookup Functions
  • Worksheets, Formatting, Formulas
  • Sorting, Filtering, Date and Time
  • Charts, Dashboards, What-if Analysis
  • Printing, Keyboard Shortcuts
  • MySQL
  • Introduction to MySQL
  • SQL Commands, Data Types, Constraints
  • Operators, Clause, SQL Statement Fundamentals
  • Group By Statements, Window Functions
  • Aggregate Functions, Joins, CTE Table, Sub-Query, Index
  • Advanced SQL Commands, Creating Databases and Tables
  • Conditional Expressions and Procedures
  • Excel Data Analysis
  • Using Excel functions for statistical and logical operations
  • SQL Querying
  • Writing SQL queries for data extraction, transformation, and reporting
  • Project Planning
  • Data Acquisition
  • Model Building
  • Development
  • Training
  • Evaluation
  • Presentation
  • Demonstration
  • End-to-End Data Science Project
  • Working on a real-world data science project from data collection to model deployment
  • Guest Lectures by renowned and eminent AI experts
  • Real-World Case Studies and Applications
  • Troubleshooting issues
  • Problem Solving
  • Interactive Sessions
  • Interactive Problem-Solving Sessions
  • Analyzing real-world case studies and applying solutions

 

Projects

These projects align with the initial modules covering Python, SQL, and Exploratory Data Analysis (EDA).

  • Skills Covered: Data cleaning, exploratory data analysis, feature engineering, and pattern recognition.
  • Objective: Analyze loan eligibility patterns for a finance company, ensuring eligible applicants are approved while minimizing default risk.
  • Tech Stack: Python (Pandas, Matplotlib, Seaborn), SQL, Power BI/Tableau.
  • Skills Covered: SQL database management, data manipulation, business intelligence.
  • Objective: Perform comprehensive analysis of Walmart’s sales data, identifying trends and sales drivers.
  • Tech Stack: SQL, Python (Pandas, Matplotlib), Tableau/Power BI.

These projects correspond to modules covering Machine Learning, Supervised/Unsupervised Learning, and Data-Driven Decision Making.

  • Skills Covered: Regression modeling, feature selection, data visualization.
  • Objective: Develop a prediction engine to determine house selling prices based on location, size, and market trends.
  • Tech Stack: Python (Scikit-learn, NumPy, Pandas), Linear Regression, Random Forest.
  • Skills Covered: Classification models, predictive analytics, and business strategy.
  • Objective: Build a model to predict customer churn for a subscription-based or telecom service, helping businesses improve retention strategies.
  • Tech Stack: Python (Scikit-learn), Logistic Regression, Decision Trees, Random Forest.
  • Skills Covered: Time series forecasting, trend analysis, feature engineering.
  • Objective: Forecast sales for a supermarket chain using historical data and external factors such as promotions and seasonal trends.
  • Tech Stack: Python (ARIMA, Prophet, Pandas), Power BI/Tableau.
  • Skills Covered: Recommendation systems, collaborative filtering, and user behavior analytics.
  • Objective: Create a system that suggests products based on purchase history and browsing behavior, enhancing user experience.
  • Tech Stack: Python (Scikit-learn, Surprise Library), Matrix Factorization, Collaborative Filtering.

These projects fit within Deep Learning, Generative AI, and Deployment modules.

  • Skills Covered: Natural Language Processing (NLP), Large Language Models (LLMs), Prompt Engineering.
  • Objective: Develop a chatbot capable of engaging in meaningful conversations and assisting users based on provided documents.
  • Tech Stack: Python (Transformers, OpenAI API, LangChain), Flask for deployment.
  • Skills Covered: Deep Learning, Neural Collaborative Filtering, AI-based recommendations.
  • Objective: Implement an advanced recommendation engine using deep learning algorithms to improve accuracy.
  • Tech Stack: Python (TensorFlow, Keras, Matrix Factorization), Neural Collaborative Filtering.

This project integrates all skills learned across EDA, ML, AI, and Business Intelligence.

  • Skills Covered: Data science, machine learning, optimization strategies, and AI-driven insights.
  • Objective: Create a comprehensive solution for retail store performance improvement by analyzing sales, inventory, and customer behavior.
  • Tech Stack: Python (Scikit-learn, XGBoost), SQL, Power BI/Tableau.

 

Certification

Career Support

We have a dedicated team which is taking care of our learners learning objectives.

FAQ

There is no such prerequisite if you are enrolling for Master’s Course as everything will start from scratch. Whether you are a working IT professional or a fresher you will find a course well planned and designed to incorporate trainee from various professional backgrounds.
AI Council offers 24/7 query resolution, you can raise a ticket with a dedicated support team and expect a revert within 24 Hrs. Email support can resolve all your query but if still it wasn’t resolved then we can schedule one-on-one session with our instructor or dedicated team. You can even contact our support after completing the training as well. There are no limits on number of tickets raised.
AI council provide two different modes for training one can choose for instructor lead training or learning with prerecorded video on demand. We also offer faculty development programs for college and schools. apart from this corporate training for organization/companies to enhance and update technical skills of the employees. We have highly qualified trainers who are working in the training industry from a very long time and have delivered the sessions and training for top colleges/schools and companies.
We are providing a 24/7 assistance for the ease of the student. Any query can be raised through the interface itself as well as can be communicated through email also. If someone is facing difficulties with above methods mentioned above we can arrange a one on one session with the trainer to help you with difficulties faced in learning. You can raise the query throughout the total training period as well as after the completion of the training.
AI Council offers you the latest, appropriate and most importantly the real-world projects throughout your training period. This makes student to gain industry level experience and converting the learning’s into solution to create the projects. Each Training Module is having Task or projects designed for the students so that you can evaluate your learning’s. You will be working on projects related to different industries such as marketing, e-commerce, automation, sales etc.
Yes, we do provide the job assistance so that a learner can apply for a job directly after the completion of the training. We have tied-ups with companies so when required we refers our students to those companies for interviews. Our team will help you to build a good resume and will trained you for your job interview.
After the successful completion of the training program and the submission of assignments/quiz, projects you have to secure at least B grade in qualifying exam, AI Council certified certificate will be awarded to you. Every certificate will be having a unique number through which same can be verified on our site.
To be very professional and transparent No, we don’t guarantee the job. the job assistance will help to provide you an opportunity to grab a dream job. The selection totally depends upon the performance of the candidate in the interview and the demand of the recruiter.
Our most of the programs are having both the modes of training i.e. instructor led and self-paced. One can choose any of the modes depending upon their work schedule. We provide flexibility to choose the type of training modes. While registering for courses you will be asked to submit your preference to select any of the modes. If any of the course is not offered in both modes so you can check in which mode, the training is going on and then you can register for the same. In any case if you feel you need any other training mode you can contact our team.
Yes, definitely you can opt for multiple courses at a time. We provide flexible timings. If you are having a desire for learning different topics while continuing with your daily hectic schedule our course timing and modes will help you a lot to carry on the learning’s.
Whenever you are enrolling in any of the courses we will send the notification you on your contact details. You will be provided with unique registration id and after successful enrollment all of the courses will be added to your account profile on our website.AI Council provides lifetime access to course content whenever needed.
A Capstone project is an outcome of the culminating learning throughout the academic years. It is the final project that represents your knowledge, efforts in the field of educational learning. It can be chosen by the mentor or by the students to come with a solution.
Yes, for obtaining the certificate of diploma programmer you have to submit the capstone project.