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Data Science Course
100% Placement Guarantee Program in Hyderabad (Ameerpet)
Our Data Science course is meticulously designed to provide you with a solid foundation in data analysis, machine learning, and data visualization. Located in the tech hub of Hyderabad, specifically in Ameerpet, our institute offers an intensive curriculum that covers Python, R, SQL, and various machine learning algorithms.
This course is perfect for those aspiring to enter the field of data science or advance their current careers. With a strong emphasis on hands-on projects, you will gain practical experience and build a portfolio that appeals to employers.
Key highlights of our program:
Expert Instructors
Learn from industry veterans with years of experience in
Data science.
Comprehensive Curriculum
Master the essentials of Data Science.
100% Placement Guarantee
Benefit from our dedicated placement support to secure your dream job.
Live Projects
Work on real-time projects to enhance your learning experience.
Curriculum
Module 1: Introduction to Data Science
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Overview of Data Science: Understanding the data science lifecycle and its applications.
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Python for Data Science: Basics of Python, libraries like NumPy, pandas.
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R for Data Science: Basics of R programming, data manipulation with dplyr.
Module 2: Data Analysis and Visualization
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Data Wrangling: Cleaning and preparing data using pandas and R.
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Exploratory Data Analysis (EDA): Using visualizations to understand data, libraries like Matplotlib, Seaborn.
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Advanced Visualization: Interactive plots using Plotly, Tableau basics.
Module 3: Statistics and Probability
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Descriptive Statistics: Mean, median, mode, variance, standard deviation.
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Inferential Statistics: Hypothesis testing, confidence intervals, p-values.
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Probability: Probability distributions, Bayes' theorem.
Module 4: Machine Learning Basics
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Supervised Learning: Linear regression, logistic regression, decision trees, random forests.
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Unsupervised Learning: Clustering (K-means, hierarchical), principal component analysis (PCA).
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Model Evaluation: Metrics like accuracy, precision, recall, F1-score, ROC curve.
Module 5: Advanced Machine Learning
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Advanced Algorithms: Support vector machines (SVM), neural networks.
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Time Series Analysis: ARIMA models, forecasting.
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Natural Language Processing (NLP): Text preprocessing, sentiment analysis.
Module 6: Big Data Technologies
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SQL for Data Science: Writing and optimizing SQL queries, joins, subqueries.
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NoSQL Databases: Introduction to MongoDB, working with NoSQL databases.
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Big Data Frameworks: Basics of Hadoop, Spark for handling large datasets.
Module 7: Capstone Project
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Project Planning: Define the project scope and requirements.
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Development: Implementing the project using all the skills learned.
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Presentation: Presenting the project, demonstrating features, and discussing challenges faced.
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Real-Time Applications: Using WebSockets to build real-time features.
Module 8: Capstone Project
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Project Planning: Define the project scope and requirements.
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Development: Implementing the project using all the skills learned.
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Presentation: Presenting the project, demonstrating features, and discussing challenges faced.
Additional Resources
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Weekly Quizzes: Assess understanding of key concepts.
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Assignments: Practical assignments to reinforce learning.
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Mentorship Sessions: Regular one-on-one sessions with mentors.
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Admissions