Best Data Science & Machine Learning training
"Python for Data Science and Machine Learning" is a comprehensive course that teaches you Python programming skills. You'll learn to use popular libraries like NumPy, Pandas, and Scikit-Learn to extract insights from data and build predictive models.
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An exhaustive curriculum designed by our industry experts which will help you to get placed in your dream IT company.
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Python for data science course in Pune covers all the Data Science libraries along with the Python skills that you will require to become a professional data scientist. This Data Science course includes Matplotlib, Web Scraping, the OOP paradigm, factor analysis, and data science projects. Our well-Industrial experienced trainers will be there to help you 24/7, and you can also available our placement assistance to apply at from startup to top MNCs Companies.
The various stages of the Data Science Lifecycle are explored in the trajectory of this course. This Data Science Course begins with an introduction to Statistics, Probability and Python. The student will then conceptualize Data Preparation, Data Cleansing, Exploratory Data Analysis, and Data Mining (Supervised and Unsupervised). Comprehend the theory behind Feature Engineering, Feature Extraction, and Feature Selection. Participants will also learn to perform Data Mining (Supervised) with Linear Regression and Predictive Modeling with Multiple Linear Regression Techniques. Data Mining Unsupervised using Clustering, Dimension Reduction, and Association Rules are also dealt with in detail.
Our curriculum for the Data Science Course will introduce you to concepts of Data Science tools, Data Science algorithms, and machine learning principles that will assist you in gaining some meaningful insights from unstructured data. During a Data Science training course, you will learn about various languages and tools, from Python to SQL, Deep learning, Machine Learning, Artificial Intelligence, Statistical Methods, data analysis, data wrangling, and Data Visualization.
"Python for Data Science and Machine Learning in Pune" course is to provide participants with the technical skills and knowledge needed to work effectively in the field of data science and machine learning using Python.
1. Python Fundamentals:
Master the fundamentals of the Python programming language, including data types, variables, operators, and control structures.
2. Data Manipulation and Analysis:
Learn how to manipulate and analyze data using Python libraries such as NumPy and Pandas.
Perform tasks like data cleaning, transformation, and aggregation.
3. Data Visualization:
Use libraries like Matplotlib and Seaborn to create meaningful and informative data visualizations, including plots, charts, and graphs.
4. Machine Learning :
Understand the fundamentals of machine learning, including supervised and unsupervised learning, feature engineering, and model evaluation.
Become proficient in using Scikit-Learn, a popular machine learning library in Python, for building and training machine learning models.
6. Supervised Learning:
Explore supervised learning algorithms for tasks like regression and classification.
Implement algorithms such as linear regression, logistic regression, decision trees, and support vector machines.
7. Unsupervised Learning:
Study unsupervised learning techniques, including clustering and dimensionality reduction.
Implement algorithms like K-Means clustering and Principal Component Analysis (PCA).
8. Model Evaluation and Hyperparameter Tuning:
Learn how to evaluate machine learning models using metrics like accuracy, precision, recall, and F1-score. Perform hyperparameter tuning to optimize model performance.
9. Data Preprocessing and Feature Engineering:
Understand the importance of data preprocessing and feature engineering in preparing data for machine learning. Apply techniques such as normalization, encoding, and feature scaling.
10. Model Deployment:
Explore techniques for deploying machine learning models to production environments, including web applications and cloud platforms.
11. Deep Learning (Optional):
Depending on the course's depth, participants may be introduced to deep learning concepts using frameworks like TensorFlow and Keras.
12. Real-World Projects:
Work on practical projects and case studies that simulate real-world data science and machine learning scenarios. Apply the knowledge and skills acquired in the course to solve complex problems.
13. Data Science Tools:
Familiarize yourself with other data science tools and libraries commonly used in the industry, such as Jupyter Notebooks for interactive data exploration.
14. Version Control:
Learn to use version control systems like Git for code management and collaboration in data science projects.
15. Data Science Workflow:
Understand the end-to-end data science workflow, from data collection and cleaning to model deployment and monitoring.
The technical objectives of this course aim to provide participants with a strong foundation in Python programming and equip them with the skills necessary to work on data science and machine learning projects. Successful completion of the course should prepare participants for roles in data analysis, machine learning engineering, and related fields.
◉ Python Programming
◉ Data Science
◉ Machine Learning
◉ Web Scrapping
◉ Data Analysis
◉ Data Manipulation
◉ Module Training
◉ Data Visualization
◉ Instructor-led Sessions
◉ Real-life Case Studies
◉ 24 x 7 Expert Support
◉ 30+ Hours Course Duration
◉ Industry Expert Faculties
◉ Free Demo Class
◉ Interview Guidance
◉ Job Oriented Training
Completing this course equips you with valuable skills sought after by organizations looking to hire data scientists and machine learning professionals.
2. What job roles can I target after completing this course?
After completing the course, you can target job roles such as Data Scientist, Machine Learning Engineer, Data Analyst, Business Intelligence Analyst, and more.
3. Is there a demand for data science and machine learning professionals in the job market?
Yes, there is a high demand for data science and machine learning professionals as organizations increasingly rely on data-driven decision-making.
4. Can I expect job placement assistance or support after completing the course?
YES, we provide offer job placement assistance, including resume reviews, interview coaching, and access to job boards. Check with the course provider for specific details.
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