Data Scientist
Statistics for Data Science
Overview
Master essential statistical concepts to analyze, interpret, and model data effectively, building a strong foundation for predictive and analytical decision-making in data science.
-
40 Hours of Learning
-
3.4K+ Learners
-
20,000+ GST
Skills You Will Learn
-
Data summarization
-
Hypothesis testing
-
Statistical modeling
-
Distribution analysis
-
Forecast trend detection
-
Statistical programming
Course Key Highlights
- Deep dive into descriptive and inferential statistics
- Apply regression for data-driven predictions
- Use probability models for pattern recognition
- Implement Bayesian methods for forecasting
- Work with SciPy and Statsmodels libraries
- Apply statistical distributions effectively
- Perform time series analysis for trends
Course Time
Includes:
-
Self-paced
Modules -
Case studies
-
Quizzes for review
-
40 Hours of Learning
Explore more Investment Banking Plans
Essential Python for
Data Science
Master the core tools and libraries for data analysis, visualization, and machine learning in Python.
Key Highlights:
- Python for data science applications
- Data wrangling with NumPy & Pandas
- Visualizations using Matplotlib & Seaborn
- ML basics with Scikit-Learn
- Jupyter Notebook for hands-on coding
Duration: 2 Weeks
Tools: Excel, Solver, Power Query
From:
INR 20,000 + GST
Data Scientist
Statistics for Data
Science
Build a solid base in descriptive, inferential, and predictive statistics for real-world data insights.
Key Highlights:
- Probability, regression & hypothesis testing
- Time series forecasting
- Bayesian & statistical modeling
- Tools: SciPy, Statsmodels
- Real-world data interpretation
Duration: 2 Weeks
Tools: Excel, Solver, Power Query
From:
INR 20,000 + GST
Data Scientist
Machine Learning for
Data Science
Dive into ML algorithms, model evaluation, and time series forecasting with real-world projects.
Key Highlights:
- Supervised & unsupervised learning
- Classification, clustering, regression
- Ensemble models: XGBoost, Random Forest
- Time series: ARIMA, LSTM
- Real-world data interpretation
Duration: 2 Weeks
Tools: Scikit-Learn, TensorFlow
From:
INR 35,000 + GST
Data Scientist
Data Visualization & Business Intelligence using Power BI
Transform raw data into compelling visual stories and business insights with Power BI dashboards and analytics tools.
Key Highlights:
- Build interactive dashboards and reports in Power BI
- Connect and integrate multiple data sources efficiently
- Use DAX functions for advanced data calculations
- Apply Power Query for data transformation and cleaning
- Create custom visuals and interactive charts
- Use AI-powered insights for advanced analytics
- Perform real-time data monitoring and reporting
Duration: 2 Weeks
Tools: Scikit-Learn, TensorFlow
From:
INR 27,500 + GST
Data Scientist
Big Data & Cloud
Computing
Learn how to process, manage, and analyze massive datasets using cutting-edge big data tools and cloud platforms like AWS, Azure, and Google Cloud.
Key Highlights:
- Understand big data concepts and architecture principles
- Work with Hadoop, Spark, and distributed computing frameworks
- Use cloud-based storage for scalable data management
- Deploy data pipelines on AWS, Azure, and GCP
- Implement serverless computing with Lambda & Azure Functions
- Process streaming data using Kafka and Flink
- Optimize queries with cloud-based data warehouses
Duration: 2 Weeks
Tools: Scikit-Learn, TensorFlow
From:
INR 40,000 + GST
Data Scientist
AI & Deep
Learning
Master the core models of AI and deep learning, from neural networks to advanced generative models using TensorFlow and PyTorch.
Key Highlights:
- Understand deep learning fundamentals and neural networks
- Build models using TensorFlow and PyTorch
- Train and optimize CNNs for image recognition
- Implement RNNs for sequence and time-series modeling
- Apply transformers for NLP and speech tasks
- Use GANs for generative AI applications
- Train models on cloud-based GPU environments
Duration: 2 Weeks
Tools: Scikit-Learn, TensorFlow
From:
INR 55,000 + GST
Data Scientist
NLP for Text
Processing
Dive into the world of Natural Language Processing (NLP) to analyze and model human language using Python and deep learning frameworks.
Key Highlights:
- Understand NLP fundamentals and text preprocessing
- Perform NER, POS tagging, and language parsing
- Implement sentiment analysis and classification models
- Use word embeddings like Word2Vec, GloVe, and FastText
- Apply topic modeling with LDA and NMF
- Build chatbots using NLP and deep learning
- Fine-tune pre-trained models with transfer learning
Duration: 2 Weeks
Tools: Scikit-Learn, TensorFlow
From:
INR 55,000 + GST
FAQs
What is the focus of this course?
This course focuses on essential statistical methods for data science, including probability, regression, and time series analysis.
Does it include hands-on learning?
Yes, you’ll apply concepts through case studies, quizzes, and practical exercises.
Which statistical libraries are covered?
The course includes practical work with SciPy and Statsmodels.
Is Bayesian statistics included?
Yes, you’ll learn to implement Bayesian methods for predictive analytics.
How is time series analysis covered?
You will explore statistical approaches to forecast trends using time series data.
