Machine Learning & Data Science With Python Course

Machine learning and Data science are evolutionary technologies. So if you update yourself you must learn the depth knowledge of machine learning and data science to the future of data demand. Recently, data science and machine learning courses are popular in Bangladesh.Machine learning is a subset of data science. Machine learning utilizes the methodologies of data science and makes an applicable output based on Data Science. Machine learning and Data Science is concatenated with each other.

Twitter, Google, Facebook, youtube, and other social media use machine learning approaches. Besides Amazon, eBay, Alibaba, and other e-commerce websites are building their web applications using machine learning and data science. In Bangladesh  Evely, Daraz, Bkash, Grammenphone and many other companies are adopting machine learning and data science.In all domains, people can learn machine learning and data science courses in Bangladesh. This field is open to all. Math, statistics, and programming knowledge are the basic skills required to learn machine learning and data science courses in Bangladesh.

If you are interested in Machine learning and Data science training in Bangladesh, Eiconik Academy is the right place. We ensure you to build your skills strong which helps your self-confidence.Eiconik Academy also offers internships after completing the  Machine learning and Data Science course in Dhaka. This course is conducted with international faculties. All the curriculums are updated with modern curriculum and technologies.

Eiconik Academy is a trusted and leading institute for learning  Artificial intelligence courses in Bangladesh.

Why Choose Eiconik Academy?

1. International Faculty

2. Online Live Interactive Class

3. Industrial Experts

4. Project Oriented Class

5. Job Oriented Training

6. Priority Basis Intern Facilities

7. Freelancing Support

8. 4 Months Training

9. 5 Project

10. 2 Mock Interviews

11.  24 Module

Python Course Module

Module 1   Dev Environment Setup
Module 2   Python Core
Module 3   Python Functions
Module 4   Python Object-Oriented Programming
Module 5   Modules and Packages
Module 6   File Handling - TXT, JSON, CSV
Module 7   Folder and Datetime Handling
Module 8   Exception Handling
Module 9   Interacting with Web - Requests
Module 10 Web Scraping - Beautiful Soup
Module 11 Web Crawling - Scrapy

Detailed Outline ML & DS

Module 1  Applied Statistics

1) Descriptive Stats
2) Inferential Stats

Module 2  Applied Probability

1) Key Concepts
2) Probability Formulas
3) Conditional Probability
4) Bayes Theorem

Module 3  Scientific Computing

1) N-Dimensional Array Computation - NumPy
2) Scientific Computation - SciPy

Module 4  Data Visualization

1) Matplotlib

Module 5  SQL for Data Science

1) MySQL Setup
2) Database
3) Tables
4) Constrains
5) Query and Nested Queries
6) Joins
7) Views

Module 6  Data Science

1) Pandas - Series
2) Pandas - DataFrame
3) Pandas - Data Cleaning & Pre-processing
4) Exploratory Data Analysis - Pandas and Seaborn

Module 7  Machine Learning - Supervised Modelling

1) Linear Regression - Regression
2) Stochastic Gradient Descent - Regression & Classification
3) Logistic Regression - Classification
4) Support Vector Machine - Regression & Classification
5) Naive Bayes - Regression & Classification
6) K Nearest Neighbors - Regression & Classification
7) Decision Tree - Regression & Classification
8) Multilayer Perceptron - Regression & Classification

Module 8  Machine Learning - Ensemble Learning

1) Bagging

    Random Forest - Regression & Classification

2) Boosting
    AdaBoost - Regression & Classification

Module 9  Machine Learning - Unsupervised Modelling

1) Clustering

    K Means

    Hierarchical
    DBSCAN

2) Dimensionality Reduction-

    Principle Component Analysis

Module 10  Image Processing

1) Image - Loading, manipulation and Saving

2) Transformation - Resizing, Rescaling, Rotation
3) Colour and Exposure Transformation
4) Feature Extraction - HOG

Module 11  Natural Language Processing

1) NLTK
2) Tokenization
3) Stop Words
4) Stemming
5) Lemmatization
6) Vectorization

Module 12  Deploying Models with Flask

2 Mock Interviews

Career Guidance - Freelancing (Upwork) and LinkedIn

Industry Project:

1) Data Mining Project
2) Time Series - Stock Market Prediction (Data)
3) Crop Disease Prediction (image)
4) Sentiment Analysis (Text)
5) Advanced House Price Prediction

1) Gain expertise with 20+ hands-on exercises

2) Job oriented real-life industry projects

3) Dedicated mentoring sessions from Industry Expert

4) International Faculty

5) Priority basis Intern Facilities

6) Freelancing support for Market place 

Focused Job Role: 

1) Machine Learning  Engineer

2) Data Scientist

3) Data Analyst

4) Data Engineer

Pre-requisites: 

1) Computer or laptop with internet connection and basic mathematic knowledge

Certificate:

Upon successful completion of the Machine Learning and Data Science Course, we will provide an industry-recognized course completion certificate that has lifelong validity.

International Collaboration: Data Core

National Collaboration: Jashore University of Science and Technology (JUST)

Membership: BASIS