Data Science with Python
Data Science is a rapidly growing field, empowering businesses with data-driven decision-making and AI-powered solutions. This comprehensive program covers fundamental to advanced topics, including data preprocessing, exploratory data analysis, machine learning, deep learning, and big data analytics using Python. Participants will gain hands-on experience with real-world datasets, statistical analysis, data visualization, and predictive modeling. The course includes practical industry projects and case studies, preparing students for roles such as data analysts, machine learning engineers, and AI specialists. Upon completion, students will be ready to work with industry-standard tools like Pandas, NumPy, Scikit-learn, TensorFlow, and more.
Software You Will Learn
- Python
- Jupyter Notebook
- Pandas, NumPy
- Matplotlib, Seaborn
- Scikit-learn
- TensorFlow & Keras
- SQL & Apache Spark
Ideal For
- Beginners looking to enter the field of data science
- IT professionals & engineers transitioning into data analytics & AI
- Business analysts & marketing professionals using data for decision-making
- Software developers looking to specialize in machine learning & AI
- Students & graduates aiming for high-demand data science roles
Career Opportunity
- Data Analyst
- Machine Learning Engineer
- Data Scientist
- AI Specialist
- Big Data Engineer
- Business Intelligence Analyst
Course Module
Python for Data Science & Data Preprocessing
- Introduction to Data Science & Career Paths
- Python Basics for Data Science
- Working with NumPy for Numerical Computation
- Pandas for Data Manipulation & Cleaning
- Data Visualization with Matplotlib & Seaborn
- Exploratory Data Analysis (EDA) & Descriptive Statistics
- Handling Missing Data & Data Cleaning Techniques
- Feature Engineering & Feature Selection
- Introduction to Databases & SQL for Data Science
- Project: Data Cleaning & Visualization on a Real-World Dataset
Statistical Analysis & Machine Learning
- Fundamentals of Probability & Statistics for Data Science
- Inferential Statistics & Hypothesis Testing
- Introduction to Machine Learning & Supervised Learning
- Linear Regression & Logistic Regression
- Decision Trees, Random Forest, & Ensemble Methods
- Model Evaluation Metrics (Accuracy, Precision, Recall, F1-Score, AUC-ROC)
- Unsupervised Learning: Clustering with K-Means & DBSCAN
- Dimensionality Reduction: PCA & t-SNE
- Time Series Analysis & Forecasting
- Project: Building a Machine Learning Model for Predictive Analytics
Deep Learning & AI
- Introduction to Neural Networks & Deep Learning
- TensorFlow & Keras for Deep Learning
- Building Deep Learning Models (MLP, CNN, RNN)
- Convolutional Neural Networks (CNN) for Image Recognition
- Recurrent Neural Networks (RNN) for Sequential Data
- Natural Language Processing (NLP) & Text Mining
- Transformer Models & Introduction to Generative AI
- Deploying Machine Learning Models Using Flask & FastAPI
- Model Optimization & Hyperparameter Tuning
- Project: Creating an AI-Powered Sentiment Analysis System
Big Data & Data Science in Business
- Introduction to Big Data & Hadoop Ecosystem
- Apache Spark for Distributed Data Processing
- Data Science for Business Decision Making
- Recommendation Systems & Collaborative Filtering
- A/B Testing for Data-Driven Marketing
- Ethics in AI & Data Science
- Final Capstone Project: End-to-End Data Science Pipeline
- Resume Building & Data Science Job Market Trends
- Mock Interview & Technical Test Preparation
- Industry Networking & Career Guidance Session
Course Study Plan
- Month 1: Python, Data Preprocessing, & EDA
- Month 2: Machine Learning Algorithms & Statistics
- Month 3: Deep Learning, AI, & Model Deployment
- Month 4: Big Data, Business Applications, & Career Readiness
Projects
- 3+ Industry Projects (Customer Analytics, AI-based Predictions, Big Data Processing)
- 10+ Hands-On Practice Labs
Materials
- 100+ Hours of recorded content for self-paced learning
Course FAQ
Do I need prior programming knowledge?
Basic Python knowledge is helpful but not mandatory. We cover Python from scratch.
Will I receive a certificate?
Yes, you will receive a Brilliant Brains Valley Data Science Certification upon completion.
Does this course prepare me for data science jobs?
Yes, this course covers all skills needed for data science, AI, and ML jobs with hands-on projects.
Will I get practical experience?
Yes, you will work on real-world datasets, industry projects, and machine learning models.
What career support is available?
Resume-building, interview prep, job placement assistance, and industry networking.
৳ 200.00
- Students: 0
- Lessons: 40
- Durations: 4
- Category: Technical Learning
