Data Science with Python Training in Pune

Skills:

Skills:

Skills:

Skills:

Python is among the most popular, widely used, versatile, and efficient languages for programming that is open source. It's easy to learn and has an extremely powerful library for analyzing and manipulating data. It is a good choice for beginners as it is utilized in scientific computing as well as other areas that require a great deal of analytical precision, like finance, oil, and gas, physics, as well as signal processing. It's a favorite option for data scientists who utilize it to create and run machine learning programs as well as other tasks related to sciences. Python can cut development duration by about 25% due to its simple syntax and simple compilation. Debugging programs are easy using Python due to the built-in debugger. Python is the largest and most well-known programming language utilized for Data Analytics. Recent research indicates that it's being viewed as one of the Next Big things and an absolute necessity for professionals who work in Data Analytics domain.

Upon completion of Data Science using Python Certificate course, you are in a position to:

• Download and analyze data with the program.
• Learn to deal with different types of information, including ordinal, categorical as for the method of codifying
• Learn data visualization
• Utilizing Python notebooks will allow you to show your step-by-step analysis of data.
• Find out more about the roles played by the job that is performed by Machine Learning Engineers. Machine Learning Engineer
• Define Machine Learning
• Use real-time data
• Learn about techniques as well as tools utilized to develop predictive models.
• Discussion about ways to incorporate Machine Learning algorithms and their applications.
• Check Your Machine Learning algorithms.
• Do the following tasks Text Mining, as well as Sentimental Analysis.
• Let's look at what we refer to as Time Series and its related concepts.
• Learn to control your business's future while staying in the moment.

Edureka offers the most efficient online course to teach Python for Data Science. Join today to join Our Data Science with Python training and to learn from the top experts in the field.

Edureka's course is a great course for people who aren't yet professionally proficient:

• Tech Leads for Developers and Programmers, architects, and developers
• Developers who wish to become engineers in machine learning.
• Analytics Managers, who manage the analysts' team
• Business Analysts who would like to understand Machine
• Learning (ML) Techniques
• Information architects who wish to know more about
• Predictive Analytics
• Professionals who are looking to develop automated models that can be used for the development of predictive models.

Edureka's Data Science with Python course in Pune prerequisites include the basic knowledge of Computer Programming Languages. The basics in Data Analysis practiced over any instruments to analyze data, such as SAS/R, can be a great advantage. Furthermore, you'll get an online course, "Python statistical techniques for the field of data science," that can be used to create the basis for an online self-paced course after registering for The Data Science with Python certification course in Pune.

CloudLab is a cloud-based Jupyter Notebook which is pre-installed with Python packages on the cloud-lab environment. It is offered by Edureka as a part of Python Data Science Course where you can execute all the in-class demos and work on real-life projects in a fluent manner. You’ll be able to access the CloudLab via your browser which requires minimal hardware configuration. In case, you get stuck in any step, our support ninja team is ready to assist 24x7.

Edureka's Data Science with Python certification course comprises of 40 case studies that will enrich your learning experience. In addition, we also have 4 Projects that will enhance your implementation skills. Below are few case studies, which are part of the Data Science with Python course curriculum: Data Science with Python Certification Case Study 1: Maple Leaves Ltd is a start-up company which makes herbs from different types of plants and its leaves. Currently, the system they use to classify the trees which they import in a batch is quite manual. A laborer from his experience decides the leaf type and subtype of the plant family. They have asked us to automate this process and remove any manual intervention from this process. You have to classify the plant leaves by various classifiers from different metrics of the leaves and to choose the best classifier for future reference. Data Science with Python Certification Case Study 2: BookRent is the largest online and offline book rental chain in India. The company charges a fixed fee per month plus rental per book. So, the company makes more money when the user rents more books. You as an ML expert must model a recommendation engine so that the user gets a recommendation of books based on the behavior of similar users. This will ensure that users are renting books based on their individual taste. The company is still unprofitable and is looking to improve both revenue and profit. Compare the Error using two approaches – User Based Vs Item Based Data Science with Python Case Study 3: Handle missing values and fit a decision tree and compare its accuracy with a random forest classifier. Predict the survival of a horse based on various observed medical conditions. Load the data from ‘horses.csv’ and observe whether it contains missing values. Replace the missing values by the most frequent value in each column. Fit a decision tree classifier and observe the accuracy. Fit a random forest classifier and observe the accuracy. Data Science with Python Case Study 4: Principal component analysis using scikit learn. Load the digits dataset from sklearn and write a helper function to plot the image. Fit a logistic regression model and observe the accuracy. Using scikit learn perform a PCA transformation such that the transformed dataset can explain 95% of the variance in the original dataset. Compare it with a model and also comment on the accuracy. Compute the confusion matrix and count the number of instances that have gone wrong. For each of the wrong sample, plot the digit along with the predicted and original label. Data Science with Python Case Study 5: Read the datafile “letterCG.data” and set all the numerical attributes as features. Split the data into train and test sets. Fit a sequence of AdaBoostClassifier with varying number of weak learners ranging from 1 to 16, keeping the max_depth as 1. Plot the accuracy on the test set against the number of weak learners, using the decision tree classifier as the base classifier.

Data Science with Python Project #1: Industry: Social Media Problem Statement: You as ML expert have to do analysis and modeling to predict the number of shares of an article given the input parameters. Actions to be performed: Load the corresponding dataset. Perform data wrangling, visualization of the data and detect the outliers, if any. Use the plotly library to draw useful insights out of data. Perform regression modeling on the dataset as well as decision tree regressor to achieve your Learning Objectives. Also, use scaling processes, PCA along with boosting techniques to optimize your model to the fullest. Data Science with Python Project #2: Industry: FMCG Problem Statement: You as an ML expert have to cluster the countries based on various sales data provided to you across years. Actions to be performed: You have to apply an unsupervised learning technique like K means or Hierarchical clustering so as to get the final solution. But before that, you have to bring the exports (in tons) of all countries down to the same scale across years. Plus, as this solution needs to be repeatable you will have to do PCA so as to get the principal components that explain the max variance.