Master Data Science with AI GANA Tech Solutions

Flexible Learning - Classroom & Online Training

Transform your career and become a data science expert with our comprehensive course. At GANA Tech Solutions, we guide you through the entire data science lifecycle, from foundational concepts to advanced machine learning and AI applications.

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Program Highlights

Exhaustive Course Curriculum

Industry-relevant course curriculum is tailored to provide practical exposure with the theory.

Top-Notch Faculty

Trainers at GANA Tech are passionate about training and carry 13+ years of industry experience.

Real-life Projects

Learners will work on real-time Data Science scenarios from various domains to get application knowledge.

Job Readiness

Intensive interview preparation from Day 1 to prepare candidates for interviews with our network of 1500+ hiring partners.

Tools and Technologies

1. Python Programming

Python is the backbone of data science:

Basics: Installing Anaconda, Python objects (lists, strings, dictionaries)
Libraries: NumPy, Pandas, Matplotlib for data analysis and visualization
Hands-On: Arrays, data frames, loops, conditionals, and user-defined functions

2. Statistics

Build a solid foundation for data-driven decisions:

Descriptive Statistics: Mean, median, mode, variance, standard deviation, IQR, range
Inferential Statistics: Central Limit Theorem, P-value, correlation, auto-correlation
Sampling & Hypothesis Testing: Z-test, T-test, ANOVA, Chi-square, confidence intervals

3. Machine Learning

Learn both supervised and unsupervised learning techniques:

Supervised Learning: Regression (linear, multiple), Classification (logistic regression, decision trees, SVMs)
Ensemble Methods: Random Forest, AdaBoost, Gradient Boosting
Unsupervised Learning: K-means clustering, hierarchical clustering
Key Concepts: Data preprocessing, model evaluation (accuracy, precision, recall, F1-score, confusion matrix), ROC curves, hyperparameter tuning

4. Deep Learning & Artificial Intelligence

Master the future of AI and neural networks:

Neural Networks: ANNs, activation functions, Perceptrons, backpropagation
Deep Learning Models: CNN, LSTM, Bi-LSTM
Frameworks: TensorFlow 2.x and PyTorch for hands-on implementation

5. Generative AI

Explore cutting-edge AI technology:

Core Concepts: Generative AI, LangChain, Vector Databases, Large Language Models (LLMs)
Transformers: Architecture, text generation, fine-tuning (single and multi-task)
Project Lifecycle: End-to-end Generative AI project implementation

6. Business Intelligence (BI) Tools

Learn to turn data into actionable insights using BI:

Modelling in Power BI
Reading data, creating dashboards, and storing data in QVD files
Visualization in Power BI

7. Real-World Projects & Career Support

Work on live projects from multiple domains

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Why Choose Our DevOps with AWS Course?

Learn industry-relevant skills in Python, AI, and Machine Learning

Hands-on experience with real-world projects

Prepare for top careers in Data Science, AI, and Analytics

Access to live projects, interview prep, and resume support

Real-Time Projects

Customer Churn Prediction

Objective: Predict which customers are likely to leave a service (telecom, banking, or e-commerce).

Tech Stack: Python, Pandas, Scikit-learn, Logistic Regression, Random Forest

Key Concepts: Data preprocessing, feature engineering, classification algorithms, model evaluation (accuracy, precision, recall, ROC-AUC).

Sales Forecasting

Objective: Predict future sales for a retail store using historical sales data.

Tech Stack: Python, Pandas, NumPy, Time Series Analysis, LSTM

Key Concepts: Data cleaning, exploratory data analysis (EDA), time series modelling, model evaluation (RMSE, MAPE).

Predictive Maintenance

Objective: Predict machine or equipment failures to reduce downtime in manufacturing.

Tech Stack: Python, Pandas, Scikit-learn, Random Forest, Gradient Boosting

Key Concepts: Supervised learning, regression/classification, feature engineering, handling missing data, predictive analytics.

Interactive Dashboard using Qlik Sense

Objective: Visualise and analyse company KPIs through a dynamic BI dashboard.

Tech Stack: Qlik Sense, Sample datasets from sales, finance, or HR

Key Concepts: Data loading, dashboard creation, charting, filtering, and storing data in QVD files.

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Frequently Asked Questions

Who can enroll in this Data Science course?

Anyone with an interest in data, analytics, or AI can enroll. The course is suitable for beginners, working professionals, and students looking to build a career in Data Science, Machine Learning, and AI.

Do you provide placement assistance?

Yes! We offer placement support, including resume building, interview preparation, mock interviews, and guidance on landing roles in Data Science, AI, and Analytics.

Will I receive a certificate after completing the course?

Yes. You will receive a Data Science and AI course completion certificate upon successfully finishing all modules and projects.

Is there a free demo session available?

Yes, you can attend a free demo class before joining the course. This helps you understand our teaching style and course structure.

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