Software and Tools:
1. Programming languages: Python, R, SQL
2. Data analysis libraries: Pandas, NumPy, Matplotlib, Scikit-learn
3. Data visualization tools: Tableau, Power BI, D3.js
4. Machine learning frameworks: TensorFlow, PyTorch, Keras
5. Big data platforms: Hadoop, Spark, NoSQL databases
6. Cloud platforms: AWS, Google Cloud, Azure
Key Topics:
1. Data Preprocessing and Visualization
2. Machine Learning (Supervised/Unsupervised)
3. Deep Learning
4. Natural Language Processing (NLP)
5. Statistical Modeling
6. Data Mining
7. Business Intelligence
8. Big Data Analytics
Program Benefits:
1. Master data science tools and technologies
2. Develop predictive models and data-driven solutions
3. Learn from industry experts
4. Work on real-world projects
5. Enhance career prospects in data science
6. Network with peers and professionals
Program Outcomes:
1. Build predictive models and data pipelines
2. Analyze and visualize complex data
3. Communicate insights effectively
4. Drive business decisions with data-driven strategies
5. Stay updated with industry trends and tools
Learning Platform:
Our program is hosted on our state-of-the-art learning management system (LMS), providing:
1. Interactive video lessons
2. Hands-on exercises and projects
3. Live instructor support
4. Peer discussion forums
5. Personalized feedback and mentorship
Project-Based Learning:
Work on real-world projects, solving business problems and developing:
1. Predictive models
2. Data visualizations
3. Data storytelling
4. Business intelligence dashboards
Career Support:
1. Resume building and review
2. Interview preparation
3. Job placement assistance
4. Industry networking events
Certification:
Upon completion, receive a certified Data Science Professional certification from Aicademy.
Duration: 6 months (part-time)
Prerequisites: Basic programming knowledge (Python/R/SQL)
