Complete Data Science & Machine Learning : From Zero To Expert

*#1 Most Popular Online Course & Internship in Data Science* You can enroll today & get certified from EasyShiksha & HawksCode.

Complete Data Science & Machine Learning : From Zero To Expert Description

Want to become a Data Science & Machine Learning expert? This Complete Data Science & ML Course covers everything from Python, AI, and Deep Learning to Data Analytics, NLP, and Big Data.

By the end of this course, you’ll have a strong foundation in Data Science and hands-on experience in real-world Machine Learning projects that will boost your career.

Class Overview:

  1. Introduction to Data Science and Machine Learning:

    • Understand the principles and concepts of data science and machine learning.

    • Explore real-world applications and use cases of data science across various industries.

  2. Python Fundamentals for Data Science:

    • Learn the basics of Python programming language and its libraries for data science, including NumPy, Pandas, and Matplotlib.

    • Master data manipulation, analysis, and visualization techniques using Python.

  3. Data Preprocessing and Cleaning:

    • Understand the importance of data preprocessing and cleaning in the data science workflow.

    • Learn techniques for handling missing data, outliers, and inconsistencies in datasets.

  4. Exploratory Data Analysis (EDA):

    • Perform exploratory data analysis to gain insights into the underlying patterns and relationships in the data.

    • Visualize data distributions, correlations, and trends using statistical methods and visualization tools.

  5. Feature Engineering and Selection:

    • Engineer new features and transform existing ones to improve model performance.

    • Select relevant features using techniques such as feature importance ranking and dimensionality reduction.

  6. Model Building and Evaluation:

    • Build predictive models using machine learning algorithms such as linear regression, logistic regression, decision trees, random forests, and gradient boosting.

    • Evaluate model performance using appropriate metrics and techniques, including cross-validation and hyperparameter tuning.

  7. Advanced Machine Learning Techniques:

    • Dive into advanced machine learning techniques such as support vector machines (SVM), neural networks, and ensemble methods.

  8. Model Deployment and Productionization:

    • Deploy trained machine learning models into production environments using containerization and cloud services.

    • Monitor model performance, scalability, and reliability in production and make necessary adjustments.

    Enroll now and unlock the full potential of data science and machine learning with the Complete Data Science and Machine Learning Course!

Course Content

course-lock Introduction To Course course-lock Python Complete Course Introduction course-lock Python Class 1 : Introduction To Python course-lock Python Class 2 : Setting Python Environment course-lock Python Class 3 : Introduction To Variables course-lock Python Class 4 : Introduction To Keywords course-lock Python Class 5 : Introduction To Datatypes course-lock Python Class 6 : ID Function course-lock Python Class 7 : Arithmetic Operator course-lock Python Class 8 : Logical Operator course-lock Python Class 9 : Comparison Operator course-lock Python Class 10 : Bitwise Operator course-lock Python Class 11 : Membership Operator course-lock Python Class 12 : Identity Operator course-lock Python Class 13 : Conditional Statements course-lock Python Class 14 : For Loop and Range Function course-lock Python Class 15 : While Loops course-lock Python Class 16 : Break and Continue course-lock Python Class 17 : Function course-lock Python Class 18 : Try Except Finally Blocks course-lock Python Class 19 : String and Functions course-lock Python Class 20 : List and Functions course-lock Python Class 21 : Tuple and Functions course-lock Python Class 22 : Dictionary and Functions course-lock Python Class 23 : Class and Object course-lock Python Class 24 : Class Methods course-lock Python Class 25 : Inheritance and its types course-lock Python Class 26 : Polymorphism and its types course-lock Python Class 27 : Encapsulation and Access Modifiers course-lock Python Class 28 : Abstraction course-lock Python Class 29 : Mini Project course-lock Complete Data Science Course course-lock Numpy Complete Course course-lock Numpy Class 1 : Import and Install course-lock Numpy Class 2 : Array and its Types course-lock Numpy Class 3 : Datatypes course-lock Numpy Class 4 : NDIM Function course-lock Numpy Class 5 : ARANGE Function course-lock Numpy Class 6 : CONCATENATE Function course-lock Numpy Class 7 : NDMIN Function course-lock Numpy Class 8 : NDITER Function course-lock Numpy Class 9 : All Functions course-lock Pandas Class 1 : Import Dataset course-lock Pandas Class 2 : Head & Tail Function course-lock Pandas Class 3 : Info Function course-lock Pandas Class 4 : Drop na Function course-lock Pandas Class 5 : Fill na Function course-lock Pandas Class 6 : Drop Duplicates Function course-lock Pandas Class 7 : Replace Values Function course-lock Matplotlib Class 1 : Import Dataset course-lock Matplotlib Class 2 : Show Function course-lock Matplotlib Class 3 : Marker Function course-lock Matplotlib Class 4 : Xlabel Ylabel Function course-lock Matplotlib Class 5 : Title Function course-lock Matplotlib Class 6 : Linestyle Linewidth Function course-lock Matplotlib Class 7 : Barplot course-lock Complete Machine Learning Introduction course-lock Machine Learning Class 1 : Linear Regression course-lock Machine Learning Class 2 : Logistics Regression course-lock Machine Learning Class 3 : Support Vector Machine course-lock Machine Learning Class 4 : KNN course-lock Machine Learning Class 5 : K Means Clustering course-lock Machine Learning Class 6 : Naive Bayes course-lock Machine Learning Class 7 : Decision Tree Classifier course-lock Machine Learning Class 8 : Random Forest

What You Need For This Course & Internship?

  • Access to Smart Phone / Computer
  • Good Internet Speed (Wifi/3G/4G)
  • Good Quality Earphones / Speakers
  • Basic Understanding of English
  • Dedication & Confidence to clear any exam

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Frequently Asked Questions

Q.Is the course 100% online? Does it require any offline classes too?

The following course is fully online, and hence there is no need for any physical classroom session. The lectures and assignments can be accessed anytime and anywhere through a smart web or mobile device.

Q.When can I start the course?

Anyone can choose a preferred course and start immediately without any delay.

Q.What are the course and session timings?

As this is a purely online course program, you can choose to learn at any time of the day and for as much time as you want. Though we follow a well-established structure and schedule, we recommend a routine for you as well. But it finally depends on you, as you have to learn.

Q.What will happen when my course is over?

If you have completed the course, you would be able to have lifetime access to it for future reference too.

Q.Can I download the notes and study material?

Yes, you can access and download the content of the course for the duration. And even have lifetime access to it for any further reference.

Q. What software/tools would be needed for the course and how can I get them?

All the software/tools that you need for the course would be shared with you during the training as and when you need them.

Q. Do I get the certificate in a hard copy?

No, only a soft copy of the certificate will be awarded, which can be downloaded and printed, if required.

Q. Iโ€™m unable to make a payment. What to do now?

You can try to make the payment through a different card or account (maybe a friend or family). If the problem persists, email us at info@easyshiksha.com

Q. The payment got deducted, but the updated transaction status is showing โ€œfailedโ€. What to do now?

Due to some technical faults, this can happen. In such a case the amount deducted will be transferred to the bank account in the next 7-10 working days. Normally the bank takes this much time to credit the amount back into your account.

Q. The payment was successful but it still shows โ€˜Buy Nowโ€™ or not showing any videos on my dashboard? What should I do?

At times, there may be a slight delay in your payment reflecting on your EasyShiksha dashboard. However, if the problem is taking longer than 30 minutes, please let us know by writing to us at info@easyshiksha.com from your registered email id, and attach the screenshot of the payment receipt or transaction history. Soon after verification from the backend, we will update the payment status.

Q. What is the refund policy?

If you have enrolled, and are facing any technical problem then you can request a refund. But once the certificate has been generated, we shall not refund that.

Q.Can I just enrol in a single course?

Yes! You surely can. To begin this, just click the course of your interest and fill in the details to enrol. You are ready to learn, once the payment is made. For the same, you earn a certificate too.

My questions are not listed above. I need further help.

Please contact us at: info@easyshiksha.com

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