Data Science Training in Vizag

• Data science lifecycle and business problem solving
• Roles: Data Analyst, Data Scientist, ML Engineer
• Tools, workflows, and project expectations

• Syntax, operators, loops, functions, and OOP basics
• Working with files, exceptions, and reusable code
• Problem solving with Python programs

• Arrays, indexing, vectorized operations, and reshaping
• Series and DataFrames for structured analysis
• Filtering, grouping, joins, and aggregations

• Handling missing values, duplicates, and inconsistent records
• Encoding, scaling, transformation, and feature preparation
• Outlier detection and data quality checks

• SELECT queries, filtering, sorting, and aggregation
• Joins, subqueries, views, and case-based analysis
• Using SQL with reporting and analytics datasets

• Descriptive statistics, probability, and distributions
• Sampling, hypothesis testing, and confidence intervals
• Correlation, covariance, and statistical inference

• Pattern detection, trend analysis, and segmentation
• EDA with Python notebooks and business questions
• Communicating findings through structured analysis

• Matplotlib and Seaborn for chart creation
• Visualization best practices and storytelling techniques
• Dashboard thinking for decision-making reports

• Supervised vs unsupervised learning
• Train-test split, model workflow, and evaluation basics
• Scikit-learn introduction and practical experimentation

• Linear regression, logistic regression, KNN, and decision trees
• Accuracy, precision, recall, F1-score, and confusion matrix
• Model comparison and performance interpretation

• K-means, hierarchical clustering, and dimensionality reduction overview
• Customer segmentation and grouping use cases
• Practical evaluation of unsupervised outputs

• Feature selection, feature creation, and transformation
• Cross-validation, hyperparameter tuning, and pipelines
• Improving model quality and reducing overfitting

• Big data concepts, Spark overview, and scalable workflows
• Introduction to NLP, time series, and recommendation ideas
• Understanding deployment, monitoring, and production thinking

• Interactive dashboard fundamentals and KPI reporting
• Case studies combining SQL, Python, and visualization
• Presenting insights for business and management stakeholders

• End-to-end capstone project with documentation and presentation
• Portfolio building, GitHub/project walkthrough support
• Resume preparation, mock interviews, and placement guidance

Duration depends on the selected weekday, weekend, classroom, or online batch. Contact Softenant for the latest schedule and timings.

Yes. Softenant offers Data Science training in Vizag/Visakhapatnam from Akkayyapalem, with flexible learning options.

No. We start from basics and move to Python, SQL, statistics, machine learning, and big data step-by-step.

Yes. You will practice data cleaning, exploratory analysis, visualization, predictive models, and portfolio-ready project workflows.

Yes. We provide resume support, mock interviews, portfolio guidance, job alerts, and placement guidance.