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PG Diploma In Data Science - ONLINE
Course Description
PG Diploma In Data Science - ONLINE
What you'll learn in this course?
This course offers a comprehensive introduction to data science, combining statistical analysis, programming, and machine learning techniques. Participants will learn to collect, clean, and analyze data to uncover insights and drive decision-making. Key topics include Python, data visualization, predictive modeling, anddata visualization, predictive modeling,and data visualization tool like power BI. Designed for beginners and professionals, the course emphasizes hands-on projects and real-world applications. Build the skills to succeed in this high-demand field.
Course Curriculum
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python introduction ,
python comments ,
python variables ,
python booleans ,
python list ,
python tuple ,
python sets ,
python Dictionaries ,
python conditional statements ,
python primitive loops ,
python functions ,
python lambda ,
python class and objects ,
PYTHON MODULES ,
python inheritance ,
python polymorphism ,
python Abstraction ,
python encapsulation ,
python pip ,
python try except ,
python file handling ,
python basic programes ,
numpy introduction ,
numpy creating arrays ,
numpy array indexing ,
numpy array slicing ,
numpy copy and view ,
numpy array shape ,
numpy array reshape ,
numpy array iterating ,
numpy array join ,
numpy array split ,
numpy array search ,
numpy array sort ,
numpy array filter ,
pandas introduction ,
pandas series ,
pandas Dataframe ,
Pandas read csv ,
pandas analyzing data ,
cleaning empty cells ,
cleaning wrong format ,
cleaning wrong data ,
removing duplicates ,
matplotlib introduction ,
matplotlib pyplot ,
matplotlib plotting ,
matplotlib markers ,
matplotlib line ,
matplotlib labels ,
matplotlib grid ,
matplotlib subplot ,
matplotlib scatter ,
matplotlib bars ,
matplotlib piecharts ,
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intoduction to statistics ,
Descriptive vs inferential statistics ,
Measures of central tendency: mean, median, mode ,
Measures of dispersion: variance, standard deviation
Probability basics ,
propability Distributions ,
Correlation and covariance ,
Central limit theorem ,
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mysql introduction ,
RDBMS ,
SQL ,
CREATE DATABASE ,
CREATE TABLE ,
MYSQL SELECT ,
MYSQL WHERE ,
MYSQL AND OR NOT ,
MYSQL ORDER BY ,
MYSQL INSERT INTO ,
MYSQL NULL VALUES ,
MYSQL UPDATE ,
MYSQL DELETE ,
MYSQL LIMIT ,
MYSQL MIN AND MAX ,
MYSQL AVG COUNT SUM ,
MYSQL LIKE ,
MYSQL IN ,BETWEEN ,
MYSQL ALTER ,
MYSQL DROP TABLE ,
MYSQL DATABASE ,
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machine learning introduction ,
PREPROCESSING ,
SUPERVISED LEARNING ,
UNSUPERVISED LEARNING ,
SEMI -SUPERVISED LEARNING ,
REINFORCEMENT LEARNING ,
CLASSIFICATION AND REGRESSION ,
CLUSTERING AND ASSOCIATION ,
LINEAR REGRESSION ,
LOGISTIC REGRESSION ,
DECISION TREE ,
OVERFITTING AND UNDERFITTING ,
ENSEMBLE METHOD ,
RANDOM FOREST ,
SUPERVECTOR MACHINE ,
K-NEAREST NEIGHBOUR ,
MODEL EVALUATION(PRECISION,RECALL,F1SCORE) ,
cross validation ,
bias-variance-tradeoff ,
hyperparameter tuning ,
PCA ,
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introduction to nlp ,
python libraries for nlp ,
Text preprocessing ,
speech recognition ,
advanced nlp(deep learning) ,
what is neural network(FORWARD AND BACKWARD PROPAGATION) ,
RECURRENT NEURAL NETWORK(RNN) ,
CONVOLUTIONAL NEURAL NETWORK(CNN) ,
Speech Recognition Hands-on Experience ,
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introduction to powerbi ,
data visualization ,
power query editor ,
DAX ,
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